Introduction

For this machine learning project, we chose to explore Spotify music and what makes a song popular because we all listen to music frequently and have specific genres that we enjoy. Something we’ve always wondered about is why we enjoy a particular song, and as a consequence, how certain songs become more popular over others. Is it the artist singing the song, the fact that we’ve heard it on the radio, the beats per minute, or is it whether the lyrics are explicit? To come up with a solution to these questions, our goal is to get to know our data thoroughly, create visualizations of the attributes of our question, run regression models to find which attributes are most relevant, select and fine tune a model, and convey our results in an easily understandable report. This brings us to our research question: can we predict a song’s popularity based on its attributes?

Loading Data and Packages

The first step of our machine learning project is simple: find a data set. Only it was not quite as simple as we anticipated. We went through a multitude of datasets to find a dataset that did not face us with problems such as too many missing values, too many observations, too little observations, and more. This process took much longer than we expected, as it comprised of downloading multiple files and attempting to upload them into git, only to discover that they didn’t satisfy all of our data needs to explore our research question.

Finally, we landed on a dataset from a Kaggle project called “Music Recommendation System using Spotify Dataset”, for which a codebook is attached in our zip files. Below, we provide the list of general packages we used for this project (model-specific packages will be included in the model-building section), along with a preview of our dataset.

# list all packages here
library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
## ✓ ggplot2 3.3.5     ✓ purrr   0.3.4
## ✓ tibble  3.1.6     ✓ dplyr   1.0.8
## ✓ tidyr   1.2.0     ✓ stringr 1.4.0
## ✓ readr   2.1.2     ✓ forcats 0.5.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()
library(knitr)
library(lubridate)
## 
## Attaching package: 'lubridate'
## The following objects are masked from 'package:base':
## 
##     date, intersect, setdiff, union
library(httpuv)
library(cluster)
library(factoextra)
## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBa
library(data.table)
## 
## Attaching package: 'data.table'
## The following objects are masked from 'package:lubridate':
## 
##     hour, isoweek, mday, minute, month, quarter, second, wday, week,
##     yday, year
## The following objects are masked from 'package:dplyr':
## 
##     between, first, last
## The following object is masked from 'package:purrr':
## 
##     transpose
library(dplyr)
library(ggplot2)
library(corrplot)
## corrplot 0.92 loaded
# load music.csv
music <- read.csv("/Users/kimbauer/Desktop/DoubleProjectGroup/131 Project/Spotify Dataset/musicdata.csv")

# music.csv preview
head(music)
##   valence year acousticness             artists danceability duration_ms energy
## 1   0.328 1960        0.547      ['Etta James']        0.274      179693  0.348
## 2   0.402 1960        0.829      ['Etta James']        0.421      196133  0.285
## 3   0.644 1960        0.764 ['Ella Fitzgerald']        0.508      175987  0.287
## 4   0.836 1960        0.733 ['Ella Fitzgerald']        0.579      131733  0.502
## 5   0.965 1960        0.699     ['Neil Sedaka']        0.743      139200  0.799
## 6   0.407 1960        0.878       ['Sam Cooke']        0.553      165560  0.291
##   explicit                     id instrumentalness key liveness loudness mode
## 1        0 4Hhv2vrOTy89HFRcjU3QOx         1.33e-02   5   0.3340   -8.631    1
## 2        0 0zGLlXbHlrAyBN1x6sY0rb         1.55e-06   2   0.2330   -9.430    0
## 3        0 4ukUoXLuFzMixyZyabSGc4         0.00e+00   1   0.1530  -12.472    1
## 4        0 65irrLqfCMRiO3p87P4C0D         0.00e+00   8   0.2810   -7.570    1
## 5        0 2x6pbpjVGjiWCcH89IK8AX         0.00e+00   8   0.0635   -5.466    0
## 6        0 0BFEyqJ9DJXS7gKg0Kj46R         0.00e+00   4   0.1290  -10.426    0
##                        name popularity release_date speechiness   tempo
## 1                   At Last         76         1960      0.0293  87.430
## 2     A Sunday Kind Of Love         70         1960      0.0293  85.861
## 3               Sleigh Ride         69       1/1/60      0.0523 154.759
## 4        Frosty The Snowman         69       1/1/60      0.0513  76.816
## 5 Breaking Up Is Hard to Do         62     12/30/60      0.0375 116.112
## 6               You Send Me         59       1/1/60      0.0301  96.217

Data Pre-processing

In our initial look at this dataset, we wanted to identify any concerns early on so that we could either address them in our data pre-processing or look for a new dataset if the concerns were too large to overcome. The first problem in our data we looked for was missing values. After running a summary of the dataset, we found that there were no NA values, which we took as a good sign. We did notice that some of the ‘release_date’ values only contained the release year and not the exact release data of the song, but we figured this would not be a problem for our exploration. Additionally, we were thrown off by the number of zero values we saw in our initial look at the data, specifically in the columns ‘explicit’ and ‘mode’, but after further examination, we realized that they were coded dummy variables, so this was not a problem for our exploration. We also determined that we did not want to drop either of these variables from our data set, as we felt that if a song is explicit or not could be influential in how popular it becomes, and we felt that if a song was in a minor key or a major key could also be influential in how popular it becomes.

Thus, we begin our data pre-processing by mutating our dummy variables explicit and mode into as.factor variables. If, for a given song, explicit = 0, we label that as “Clean”, and if explicit = 1, we label that “Explicit”. If, for a given song, mode = 0, we label that as “Minor”, and if mode = 1, we label that as “Major”.

# mutate our dummy variables into as.factor
# music = music %>% 
#   mutate(explicit = as.factor(ifelse(explicit == 0, "Clean", "Explicit"))) %>% 
#   mutate(mode = as.factor(ifelse(mode == 0, "Minor", "Major")))

As our research question requires us to take a regression approach, we did have a concern of our data having too many categorical variables to fit into our regressive model with this data. To address this problem, we thought about what variables would be most important to our data exploration. One of the variables that we thought would be most important to include was ‘artists’, as we know that the artist of a song can have a direct impact on the song’s popularity: a more popular artist is more likely to release a song that has higher popularity, and vice versa. With the artists column being string-valued categorical observations, and with there being so many different artists in our data, we wanted to find a way to incorporate this variable into our data as a unique but quantitative variable. We decided that this would be the next step of our data mutation

In order to keep the important variable of artists but make it quantitative, we decided to take the average song popularity by each artist in the data, and assign that variable of average artist popularity to each artist as a new variable in the dataset. Thus, our dataset would lose the column ‘artists’ containing each artist’s name, and instead assign the variable avg_art_pop as the artist’s average song popularity. This variable mutation process is outlined in the code chunk below.

## manipulation of 'artist' variable

# create a new table that aggregates the variables popularity and artists and finds the mean song popularity for each given artist
artist_pop_table <- aggregate(music$popularity, list(music$artists), FUN = mean)

# merges the table above into our music dataset by artist
full_merge <- merge(x = music, y = artist_pop_table, by.x = c("artists"), by.y = c("Group.1"), all.x = TRUE)

# rename full dataset and x column
full_data <- rename(full_merge, avg_art_pop = x)

# delete previous 'artist' column
delete1 <- c("artists")
full_data <- full_data[!(names(full_data) %in% delete1)]
head(full_data)
##   valence year acousticness danceability duration_ms energy explicit
## 1   0.460 2012       0.0280        0.730      279080  0.682        1
## 2   0.841 1964       0.0589        0.681      177427  0.499        0
## 3   0.952 1966       0.1460        0.616      133413  0.881        0
## 4   0.827 1966       0.1410        0.659      131480  0.573        0
## 5   0.678 1966       0.5060        0.776      149267  0.764        0
## 6   0.963 1966       0.1050        0.646      170827  0.926        0
##                       id instrumentalness key liveness loudness mode
## 1 55iiBrGOWT5W99VKy4Fk2C         2.87e-06   7   0.1140   -4.517    1
## 2 4v75K5mEyumdXCZU09kwAg         6.39e-06   7   0.0743   -6.894    1
## 3 63Vw8PU3ps8TAxDdHAUTMX         7.52e-01   5   0.0643   -6.357    1
## 4 40NHppXZVM0eYvsVseywWl         9.70e-05   2   0.0779  -10.183    1
## 5 0HmDZd0eP9PVMaZggRp6Em         0.00e+00   0   0.1760   -8.336    1
## 6 23MXQSnv6ZrZUiLy6DdnYl         8.00e-01   0   0.0884   -5.933    1
##                     name popularity release_date speechiness   tempo
## 1               Badlands         46      3/26/12      0.1430 147.988
## 2               96 Tears         42       1/1/64      0.0340 123.458
## 3        I Need Somebody         23         1966      0.0372 134.048
## 4            Ten O'clock         16         1966      0.0336  96.254
## 5 You're Telling Me Lies         15         1966      0.0802  88.574
## 6                Up Side         26         1966      0.0426 125.672
##   avg_art_pop
## 1    46.00000
## 2    25.11111
## 3    25.11111
## 4    25.11111
## 5    25.11111
## 6    25.11111

In addressing the multiple categorical variables we had left in our dataset, we then set out to determine if these variables would be important to our exploration and if they would be feasible to incorporate quantitatively into our data (similar to artists above). The qualitative variables that we had left in our dataset (that we decided would be irrational to dummy code) were id, key, name, release_date. We discussed each of these variables as a group, and decided that none of them would be very useful to try and fit quantitatively into our final data set, as we don’t feel they will logically be important in predicting a given song’s average popularity. In addition, analysis of the plots of some of these variables, such as key, demonstrate no real key being favored over others (see Exploratory Data Anallysis). Thus, we decided to drop these variables from our dataset, as shown below.

# delete variables that will not be useful in our exploration
delete2 <- c("id", "key", "name", "release_date")
full_data <- full_data[!(names(full_data) %in% delete2)]

And finally, after making sure that all of our quantitative variables were numeric (shown in code chunk below), our data was ready for some exploratory data analysis.

# mutating leftover int variables to num type
full_data$popularity <- as.numeric(full_data$popularity)
full_data$year <- as.numeric(full_data$year)
full_data$duration_ms <- as.numeric(full_data$duration_ms)

Exploratory Data Analysis

We first set out to explore the relationship between the various predictors and the response variable, popularity. We first subset the data to a more manageable size so that we could discern something from exploratory data analysis:

set.seed((123))
# sample data to use for exploratory graphics
sample <- full_data[sample(nrow(full_data), 200), ]

COMMENT: TO KEY OR NOT TO KEY, DEBATE LATER IF TIME

After defining our various plots, we accumulate them into a panel for better visibility:

# library(patchwork)
# valence + year + acousticness
# danceability + duration + energy
# explicit + instrumentalness +  key
# liveness +  loudness + mode
# speechiness +  tempo + avg_art_pop
library(ggpubr)
figure <- ggarrange(valence, year, acousticness, danceability, duration, energy, explicit, instrumentalness, liveness, loudness, mode, speechiness, tempo, avg_art_pop, ncol = 3, nrow = 5)
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
figure

There are several things that can be extrapolated from the panel of plots: mainly, many of the predictors, such as valence, acousticness, danceability, duration_ms, and tempo all have fairly weak correlations with popularity. We also learn that many songs in the dataset appear to be around 0 for speechiness, liveness, and acousticness. Regarding the categorical variables explicit and mode, there is a clear skew towards songs that are clean and in a major key.

Looking specifically at the variables that have the strongest relationships with popularity, the two predictors year and avg_art_pop appear to have the strongest positive correlation with popularity. This makes intuitive sense.

There are several factors that could explain why year has a positive, near linear, relationship with popularity: for one, the population has increased from the 1960s until present day. With more people comes a more active listening base for artists to reach. In addition, the methods by which we obtain music have changed over the decades, starting off with things like records and record players, CDs, iTunes, and now with music streaming through platforms like Spotify.

It makes intuitive sense why an artist’s average popularity would be positively correlated with popularity. An artist with high brand value or recognition, such as Kendrick Lamar, Ariana Grande, or Justin Bieber are more likely to have new releases listened to by significantly more people as opposed to a more obscure or lesser known artist such as Gus Dapperton or Peach Pit.

This relationship is clearly shown through a correlation matrix and subsequent heatmap:

# making some of the int variables into numeric
full_data$popularity <- as.numeric(full_data$popularity)
full_data$year <- as.numeric(full_data$year)
full_data$duration_ms <- as.numeric(full_data$duration_ms)

# mutating dummy variables 
full_data2 = full_data %>% 
  mutate(explicit = as.factor(ifelse(explicit == 0, "Clean", "Explicit"))) %>% 
  mutate(mode = as.factor(ifelse(mode == 0, "Minor", "Major")))

# modifying our full data to leave out the variables we don't want
delete <- c("artists", "id", "key", "name", "release_date")
full_data <- full_data[!(names(full_data) %in% delete)]
# correlation matrix and heatmap
library(corrplot)
corr_mat <- cor(full_data)
corr_mat[, 12]
##          valence             year     acousticness     danceability 
##      -0.05766409       0.68198486      -0.24959846       0.18750900 
##      duration_ms           energy         explicit instrumentalness 
##      -0.02197240       0.19717541       0.26782335      -0.14840380 
##         liveness         loudness             mode       popularity 
##      -0.07600035       0.31230798      -0.06658299       1.00000000 
##      speechiness            tempo      avg_art_pop 
##       0.10043080       0.03306722       0.81967675
corrplot(corr_mat, type = "lower", order = "hclust", tl.col = "black", tl.srt = 45)

The heatmap reinforces the notion that the two predictors with the strongest positive association with popularity are year and avg_art_pop. We thus have reason to believe that they will be influential and important to include in our model building.

Finally, an analysis of the distribution of the response popularity allows us to see that it is pretty normally-distributed.

# adding a density histogram for our outcome variable popularity
hist <- ggplot(full_data) + 
  ggtitle("Density Histogram for Outcome Varible") + # include title
  geom_histogram(aes(popularity, y = after_stat(density)), binwidth = 5, fill = "cyan", color = "grey")  # add histogram w density
x <- seq(0, 100, length.out = 100)
df <- with(full_data, data.frame(x=x, y = dnorm(x, mean(popularity), sd(popularity))))
hist + geom_line(data = df, aes(x = x, y = y), color = "red")

Model Fitting

Now that we have explored our data visually, we can begin to form our models. We looked the characteristics of our data, such as the number of observations, type of data (qualitative vs quantitative), etcetera, and found that an elastic net model, a Bayesian additive regression trees (BART) model, a multivariate adaptive regression splines (MARS) model, and a k-nearest neighbors (KNN) model would suit our research question and data well. Each of these algorithms fit our regression-based question well. We will explore the reasons why we chose each model later in this section.

Splitting our data

Since we have 120,750 observations (songs) in total, we can safely split our dataset into train and test sets. This way we can use the training data to fit our model and save the test data to evaluate how well our model predicts the data (test MSE). We chose to use 70% of the data for training and 30% of the data for testing. To implement this, we set the seed for reproductability, took a random sample of 70% of the dataset, and used that sample to create a training set. The rest of the values were used for the testing set. Below is an illustration of how the elastic net uses both the lasso and ridge techniques.

# split training and testing data
#set seed
set.seed(123)
# Sample 70% of observations as training data 
trainsample = sort(sample(nrow(full_data), nrow(full_data)*.7))
# define dat.train as the 70% of observaions
train = full_data[trainsample,]
# The rest as test data
test = full_data[-trainsample,]

K-NN

The k-nearest neighbors regression algorithm is a non-parametric method that takes observations from different neighbors to approximate the association between the predictors and the outcome (in our case song popularity). KNN is a good fit for our research question because the function can have many function forms other than linear, which is what we are looking for.

The downside about that KNN algorithm is that it can only be used when the variances of variables are similar. By using this model, we are making the assumption that the variances of each predictor of probability are similar enough. Further, KNN makes it difficult to “predict into the future”, which, alongside the curse of dimensionality, makes it not very interpretable.

For the KNN model, our tuning parameter is k.

To implement our model, we first load the required packages and use the do.chunk() function for k-fold cross-validation. We use folddef to specify an index to map all observations in the design matrix and all observations into the response into a set of k folds. chunkid is used to set the fold used as the validation set. The do.chunk function as a whole trains the model using all folds but the chunkid fold, and computes the validation error for that last fold. The resulting dataframe consists of all possible values of the folds with their test error rate.

library(ISLR)
library(tidyverse)
library(class)
library(FNN)
## 
## Attaching package: 'FNN'
## The following objects are masked from 'package:class':
## 
##     knn, knn.cv
do.chunk <- function(chunkid, folddef, Xdat, Ydat){
  train = (folddef!= chunkid)

  Xtr = Xdat[train,]
  Ytr = Ydat[train]

  Xval = Xdat[!train,]
  Yval = Ydat[!train]
  
  predYtr = knn(train = Xtr, test = Xtr, cl = Ytr)
  predYvl = knn(train = Xtr, test = Xval, cl = Ytr)

  data.frame(fold = chunkid,
             train.error = mean(predYtr != Ytr),
             val.error = mean(predYvl != Yval))
}

Next, we specify that we would like 10 folds and divide the data into ten intervals.

nfold = 10
set.seed(100)
folds = cut(1:nrow(train), breaks = nfold, labels = FALSE) %>% sample()

Next, we decide to have 50 neighbors considered, and loop through all 50 of the neighbor for each different chunk id. Below is a dataframe of the error folds and their respective training error, validation error, and neighbors.

error.folds = NULL
# Give possible number of nearest neighbours to be considered
allK = 1:50
# Set seed since do.chunk() contains a random component induced by knn()
set.seed(888)


Ytrainknn <- train$popularity %>% scale(center = TRUE, scale = TRUE) # from lab 5
Xtrainknn <- train %>% select(-popularity) %>% scale(center = TRUE, scale = TRUE)

Ytestknn <- test$popularity %>% scale(center = TRUE, scale = TRUE)
Xtestknn <- test %>% select(-popularity) %>% scale(center = TRUE, scale = TRUE)


Xtrainknn = unlist(Xtrainknn) # unlist to convert from list to vector
Ytrainknn = unlist(Ytrainknn)
# Loop through different number of neighbors
for (k in allK){
# Loop through different chunk id 
  for (j in seq(3)){
    tmp = do.chunk(chunkid=j, folddef=folds, Xdat=Xtrainknn,
                   Ydat=Ytrainknn)
    tmp$neighbors = k # Record the last number of neighbor
    error.folds = rbind(error.folds, tmp) # combine results }
  }
}

head(error.folds, 10)
##    fold train.error val.error neighbors
## 1     1 0.008649700 0.9558737         1
## 2     2 0.009043945 0.9504259         1
## 3     3 0.009030918 0.9564652         1
## 4     1 0.008649700 0.9558737         2
## 5     2 0.009043945 0.9504259         2
## 6     3 0.009030918 0.9564652         2
## 7     1 0.008649700 0.9558737         3
## 8     2 0.009043945 0.9504259         3
## 9     3 0.009030918 0.9564652         3
## 10    1 0.008649700 0.9558737         4

Next, we want to decide the optimal k for kNN, using error.folds. We want the type (training or test) of error and the corresponding value for each fold and each neighbor. We can do this using the melt() function.

# Transform the format of error.folds for further convenience
errors = melt(error.folds, id.vars=c('fold', 'neighbors'), value.name='error')
## Warning in melt(error.folds, id.vars = c("fold", "neighbors"), value.name =
## "error"): The melt generic in data.table has been passed a data.frame and will
## attempt to redirect to the relevant reshape2 method; please note that reshape2
## is deprecated, and this redirection is now deprecated as well. To continue using
## melt methods from reshape2 while both libraries are attached, e.g. melt.list,
## you can prepend the namespace like reshape2::melt(error.folds). In the next
## version, this warning will become an error.
# Choose the number of neighbors which minimizes validation error
val.error.means = errors %>%
# Select all rows of validation errors 
  filter(variable=='val.error') %>%
# Group the selected data frame by neighbors 
  group_by(neighbors, variable) %>%
# Calculate CV error rate for each k 
  summarise_each(funs(mean), error) %>%
# Remove existing group
  ungroup() %>%
  filter(error==min(error))
## Warning: `summarise_each_()` was deprecated in dplyr 0.7.0.
## Please use `across()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.
## Warning: `funs()` was deprecated in dplyr 0.8.0.
## Please use a list of either functions or lambdas: 
## 
##   # Simple named list: 
##   list(mean = mean, median = median)
## 
##   # Auto named with `tibble::lst()`: 
##   tibble::lst(mean, median)
## 
##   # Using lambdas
##   list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was generated.
# Best number of neighbors
# if there is a tie, pick larger number of neighbors for simpler model 
numneighbor = max(val.error.means$neighbors)
numneighbor
## [1] 50

Thus, we found that a [insert here]-NN classifier would be best. Now we can calculate the test MSE using the knn function.

# train knn regressor and make predictions on training set using k=20
pred.Ytrainknn = knn.reg(train = Xtrainknn, test = Xtrainknn, y = Ytrainknn, k = numneighbor)
# head(pred.Ytrainknn)
# get training MSE
mean((pred.Ytrainknn$pred - Ytrainknn)^2)
## [1] 0.3291254
# now make predictions on test set (just to have predict code)
Ytrain <- as.data.frame(Ytrainknn)
pred.Ytestknn = knn.reg(train = Xtrainknn, test = Xtestknn, y = Ytrainknn, k = numneighbor)
head((pred.Ytestknn$pred - Ytestknn)^2)
##            [,1]
## [1,] 0.77009409
## [2,] 0.26824619
## [3,] 0.84019685
## [4,] 0.08707421
## [5,] 0.11665845
## [6,] 0.18884455
mean((pred.Ytestknn$pred - Ytestknn)^2)
## [1] 0.3474553

Thus, we found or training MSE to be 0.3100 and our test MSE to be 0.3490 for this model. This is a considerably low MSE, and the training and test MSEs being so similar leads us to believe that the k-NN model properly prevented overfitting.

Elastic Net Model Fitting

Our next model is the elastic net, a combination of the ridge and lasso techniques. The elastic net method is a regularized linear regression that combines L1 and L2 penalty functions from the lasso and ridge techniques. Thus, the elastic net performs variable selection and regularization simultaneously. We found the elastic net to be more ideal than the ridge and lasso techniques on their own because it uses both methods and learns from them.

The idea of the elastic net is to minimize the residual sum of squares and add a penalty term:

\[\sum\limits_{i=1}^n (y_i - \beta_0 - \sum\limits_{j=1}^p \beta_j x_{ij})^2 + \lambda[(1 - \alpha)\ ||\beta||_2^2/2 + \alpha\ ||\beta||_1]\] where \(||\beta||_1\) takes the form of L1 (L1 norm): \[||\beta||_1 = \sum\limits_{j=1}^p |\beta_j|\]

and \(||\beta||_2\) takes the form of L2 (Euclidean norm): \[||\beta||_2 = \sqrt{\sum\limits_{j=1}^p \beta_j^2}\] Here is a visual explanation of the elastic net: elastic net implementation.

This model was a good choice for our data because it’s a regression model, which fits our mostly quantitative variables, and it improves on the lasso and ridge techniques. Additionally, the lasso and ridge methods account for collinearity, so that eliminates our need to investigate collinearity between predictors.

# load packages
library(dplyr) # data manipulation
library(glmnet) # elastic net 
## Loading required package: Matrix
## 
## Attaching package: 'Matrix'
## The following objects are masked from 'package:tidyr':
## 
##     expand, pack, unpack
## Loaded glmnet 4.1-3
library(ggplot2) # for visualization
library(caret) # classofication and regression training
## Loading required package: lattice
## 
## Attaching package: 'caret'
## The following object is masked from 'package:purrr':
## 
##     lift
# creating new train and test sets as matrices (from lab 5)
el_X <- model.matrix(popularity ~ ., full_data)[, -1]
el_Y <- full_data$popularity
set.seed(123)
eltrain = sort(sample(nrow(el_X), nrow(el_X)*.7)) # same as train sample above
eltest = (-eltrain)
x.eltrain = el_X[eltrain,]
y.eltrain = el_Y[eltrain]
x.eltest = el_X[eltest,]
y.eltest = el_Y[eltest]

# model building on training sets
control <- trainControl(method = "repeatedcv", 
                        number = 5, # 5 fold
                        repeats = 5, # 5 repeats
                        search = "random", 
                        verboseIter = TRUE)
# training elastic net regression model
elastic_model <- train(x = x.eltrain, y = y.eltrain,
                       method = "glmnet",
                       preProcess = c("center", "scale"),
                       tuneLength = 25, # tuning the model
                       trControl = control) # our cross-validation defined above
## + Fold1.Rep1: alpha=0.88673, lambda=0.188648 
## - Fold1.Rep1: alpha=0.88673, lambda=0.188648 
## + Fold1.Rep1: alpha=0.17251, lambda=0.149375 
## - Fold1.Rep1: alpha=0.17251, lambda=0.149375 
## + Fold1.Rep1: alpha=0.52333, lambda=0.072676 
## - Fold1.Rep1: alpha=0.52333, lambda=0.072676 
## + Fold1.Rep1: alpha=0.89036, lambda=3.971283 
## - Fold1.Rep1: alpha=0.89036, lambda=3.971283 
## + Fold1.Rep1: alpha=0.06876, lambda=0.113433 
## - Fold1.Rep1: alpha=0.06876, lambda=0.113433 
## + Fold1.Rep1: alpha=0.69652, lambda=0.001657 
## - Fold1.Rep1: alpha=0.69652, lambda=0.001657 
## + Fold1.Rep1: alpha=0.82268, lambda=1.898387 
## - Fold1.Rep1: alpha=0.82268, lambda=1.898387 
## + Fold1.Rep1: alpha=0.35681, lambda=0.001551 
## - Fold1.Rep1: alpha=0.35681, lambda=0.001551 
## + Fold1.Rep1: alpha=0.83235, lambda=2.524038 
## - Fold1.Rep1: alpha=0.83235, lambda=2.524038 
## + Fold1.Rep1: alpha=0.88216, lambda=0.001899 
## - Fold1.Rep1: alpha=0.88216, lambda=0.001899 
## + Fold1.Rep1: alpha=0.55337, lambda=2.737403 
## - Fold1.Rep1: alpha=0.55337, lambda=2.737403 
## + Fold1.Rep1: alpha=0.82978, lambda=0.154434 
## - Fold1.Rep1: alpha=0.82978, lambda=0.154434 
## + Fold1.Rep1: alpha=0.31549, lambda=7.029301 
## - Fold1.Rep1: alpha=0.31549, lambda=7.029301 
## + Fold1.Rep1: alpha=0.89748, lambda=0.020774 
## - Fold1.Rep1: alpha=0.89748, lambda=0.020774 
## + Fold1.Rep1: alpha=0.58332, lambda=0.008189 
## - Fold1.Rep1: alpha=0.58332, lambda=0.008189 
## + Fold1.Rep1: alpha=0.66370, lambda=0.005494 
## - Fold1.Rep1: alpha=0.66370, lambda=0.005494 
## + Fold1.Rep1: alpha=0.87945, lambda=0.008348 
## - Fold1.Rep1: alpha=0.87945, lambda=0.008348 
## + Fold1.Rep1: alpha=0.39224, lambda=4.100786 
## - Fold1.Rep1: alpha=0.39224, lambda=4.100786 
## + Fold1.Rep1: alpha=0.21126, lambda=3.394816 
## - Fold1.Rep1: alpha=0.21126, lambda=3.394816 
## + Fold1.Rep1: alpha=0.20867, lambda=1.714738 
## - Fold1.Rep1: alpha=0.20867, lambda=1.714738 
## + Fold1.Rep1: alpha=0.29287, lambda=0.465785 
## - Fold1.Rep1: alpha=0.29287, lambda=0.465785 
## + Fold1.Rep1: alpha=0.81856, lambda=0.021962 
## - Fold1.Rep1: alpha=0.81856, lambda=0.021962 
## + Fold1.Rep1: alpha=0.66803, lambda=6.064987 
## - Fold1.Rep1: alpha=0.66803, lambda=6.064987 
## + Fold1.Rep1: alpha=0.48714, lambda=0.971740 
## - Fold1.Rep1: alpha=0.48714, lambda=0.971740 
## + Fold1.Rep1: alpha=0.53708, lambda=0.217687 
## - Fold1.Rep1: alpha=0.53708, lambda=0.217687 
## + Fold2.Rep1: alpha=0.88673, lambda=0.188648 
## - Fold2.Rep1: alpha=0.88673, lambda=0.188648 
## + Fold2.Rep1: alpha=0.17251, lambda=0.149375 
## - Fold2.Rep1: alpha=0.17251, lambda=0.149375 
## + Fold2.Rep1: alpha=0.52333, lambda=0.072676 
## - Fold2.Rep1: alpha=0.52333, lambda=0.072676 
## + Fold2.Rep1: alpha=0.89036, lambda=3.971283 
## - Fold2.Rep1: alpha=0.89036, lambda=3.971283 
## + Fold2.Rep1: alpha=0.06876, lambda=0.113433 
## - Fold2.Rep1: alpha=0.06876, lambda=0.113433 
## + Fold2.Rep1: alpha=0.69652, lambda=0.001657 
## - Fold2.Rep1: alpha=0.69652, lambda=0.001657 
## + Fold2.Rep1: alpha=0.82268, lambda=1.898387 
## - Fold2.Rep1: alpha=0.82268, lambda=1.898387 
## + Fold2.Rep1: alpha=0.35681, lambda=0.001551 
## - Fold2.Rep1: alpha=0.35681, lambda=0.001551 
## + Fold2.Rep1: alpha=0.83235, lambda=2.524038 
## - Fold2.Rep1: alpha=0.83235, lambda=2.524038 
## + Fold2.Rep1: alpha=0.88216, lambda=0.001899 
## - Fold2.Rep1: alpha=0.88216, lambda=0.001899 
## + Fold2.Rep1: alpha=0.55337, lambda=2.737403 
## - Fold2.Rep1: alpha=0.55337, lambda=2.737403 
## + Fold2.Rep1: alpha=0.82978, lambda=0.154434 
## - Fold2.Rep1: alpha=0.82978, lambda=0.154434 
## + Fold2.Rep1: alpha=0.31549, lambda=7.029301 
## - Fold2.Rep1: alpha=0.31549, lambda=7.029301 
## + Fold2.Rep1: alpha=0.89748, lambda=0.020774 
## - Fold2.Rep1: alpha=0.89748, lambda=0.020774 
## + Fold2.Rep1: alpha=0.58332, lambda=0.008189 
## - Fold2.Rep1: alpha=0.58332, lambda=0.008189 
## + Fold2.Rep1: alpha=0.66370, lambda=0.005494 
## - Fold2.Rep1: alpha=0.66370, lambda=0.005494 
## + Fold2.Rep1: alpha=0.87945, lambda=0.008348 
## - Fold2.Rep1: alpha=0.87945, lambda=0.008348 
## + Fold2.Rep1: alpha=0.39224, lambda=4.100786 
## - Fold2.Rep1: alpha=0.39224, lambda=4.100786 
## + Fold2.Rep1: alpha=0.21126, lambda=3.394816 
## - Fold2.Rep1: alpha=0.21126, lambda=3.394816 
## + Fold2.Rep1: alpha=0.20867, lambda=1.714738 
## - Fold2.Rep1: alpha=0.20867, lambda=1.714738 
## + Fold2.Rep1: alpha=0.29287, lambda=0.465785 
## - Fold2.Rep1: alpha=0.29287, lambda=0.465785 
## + Fold2.Rep1: alpha=0.81856, lambda=0.021962 
## - Fold2.Rep1: alpha=0.81856, lambda=0.021962 
## + Fold2.Rep1: alpha=0.66803, lambda=6.064987 
## - Fold2.Rep1: alpha=0.66803, lambda=6.064987 
## + Fold2.Rep1: alpha=0.48714, lambda=0.971740 
## - Fold2.Rep1: alpha=0.48714, lambda=0.971740 
## + Fold2.Rep1: alpha=0.53708, lambda=0.217687 
## - Fold2.Rep1: alpha=0.53708, lambda=0.217687 
## + Fold3.Rep1: alpha=0.88673, lambda=0.188648 
## - Fold3.Rep1: alpha=0.88673, lambda=0.188648 
## + Fold3.Rep1: alpha=0.17251, lambda=0.149375 
## - Fold3.Rep1: alpha=0.17251, lambda=0.149375 
## + Fold3.Rep1: alpha=0.52333, lambda=0.072676 
## - Fold3.Rep1: alpha=0.52333, lambda=0.072676 
## + Fold3.Rep1: alpha=0.89036, lambda=3.971283 
## - Fold3.Rep1: alpha=0.89036, lambda=3.971283 
## + Fold3.Rep1: alpha=0.06876, lambda=0.113433 
## - Fold3.Rep1: alpha=0.06876, lambda=0.113433 
## + Fold3.Rep1: alpha=0.69652, lambda=0.001657 
## - Fold3.Rep1: alpha=0.69652, lambda=0.001657 
## + Fold3.Rep1: alpha=0.82268, lambda=1.898387 
## - Fold3.Rep1: alpha=0.82268, lambda=1.898387 
## + Fold3.Rep1: alpha=0.35681, lambda=0.001551 
## - Fold3.Rep1: alpha=0.35681, lambda=0.001551 
## + Fold3.Rep1: alpha=0.83235, lambda=2.524038 
## - Fold3.Rep1: alpha=0.83235, lambda=2.524038 
## + Fold3.Rep1: alpha=0.88216, lambda=0.001899 
## - Fold3.Rep1: alpha=0.88216, lambda=0.001899 
## + Fold3.Rep1: alpha=0.55337, lambda=2.737403 
## - Fold3.Rep1: alpha=0.55337, lambda=2.737403 
## + Fold3.Rep1: alpha=0.82978, lambda=0.154434 
## - Fold3.Rep1: alpha=0.82978, lambda=0.154434 
## + Fold3.Rep1: alpha=0.31549, lambda=7.029301 
## - Fold3.Rep1: alpha=0.31549, lambda=7.029301 
## + Fold3.Rep1: alpha=0.89748, lambda=0.020774 
## - Fold3.Rep1: alpha=0.89748, lambda=0.020774 
## + Fold3.Rep1: alpha=0.58332, lambda=0.008189 
## - Fold3.Rep1: alpha=0.58332, lambda=0.008189 
## + Fold3.Rep1: alpha=0.66370, lambda=0.005494 
## - Fold3.Rep1: alpha=0.66370, lambda=0.005494 
## + Fold3.Rep1: alpha=0.87945, lambda=0.008348 
## - Fold3.Rep1: alpha=0.87945, lambda=0.008348 
## + Fold3.Rep1: alpha=0.39224, lambda=4.100786 
## - Fold3.Rep1: alpha=0.39224, lambda=4.100786 
## + Fold3.Rep1: alpha=0.21126, lambda=3.394816 
## - Fold3.Rep1: alpha=0.21126, lambda=3.394816 
## + Fold3.Rep1: alpha=0.20867, lambda=1.714738 
## - Fold3.Rep1: alpha=0.20867, lambda=1.714738 
## + Fold3.Rep1: alpha=0.29287, lambda=0.465785 
## - Fold3.Rep1: alpha=0.29287, lambda=0.465785 
## + Fold3.Rep1: alpha=0.81856, lambda=0.021962 
## - Fold3.Rep1: alpha=0.81856, lambda=0.021962 
## + Fold3.Rep1: alpha=0.66803, lambda=6.064987 
## - Fold3.Rep1: alpha=0.66803, lambda=6.064987 
## + Fold3.Rep1: alpha=0.48714, lambda=0.971740 
## - Fold3.Rep1: alpha=0.48714, lambda=0.971740 
## + Fold3.Rep1: alpha=0.53708, lambda=0.217687 
## - Fold3.Rep1: alpha=0.53708, lambda=0.217687 
## + Fold4.Rep1: alpha=0.88673, lambda=0.188648 
## - Fold4.Rep1: alpha=0.88673, lambda=0.188648 
## + Fold4.Rep1: alpha=0.17251, lambda=0.149375 
## - Fold4.Rep1: alpha=0.17251, lambda=0.149375 
## + Fold4.Rep1: alpha=0.52333, lambda=0.072676 
## - Fold4.Rep1: alpha=0.52333, lambda=0.072676 
## + Fold4.Rep1: alpha=0.89036, lambda=3.971283 
## - Fold4.Rep1: alpha=0.89036, lambda=3.971283 
## + Fold4.Rep1: alpha=0.06876, lambda=0.113433 
## - Fold4.Rep1: alpha=0.06876, lambda=0.113433 
## + Fold4.Rep1: alpha=0.69652, lambda=0.001657 
## - Fold4.Rep1: alpha=0.69652, lambda=0.001657 
## + Fold4.Rep1: alpha=0.82268, lambda=1.898387 
## - Fold4.Rep1: alpha=0.82268, lambda=1.898387 
## + Fold4.Rep1: alpha=0.35681, lambda=0.001551 
## - Fold4.Rep1: alpha=0.35681, lambda=0.001551 
## + Fold4.Rep1: alpha=0.83235, lambda=2.524038 
## - Fold4.Rep1: alpha=0.83235, lambda=2.524038 
## + Fold4.Rep1: alpha=0.88216, lambda=0.001899 
## - Fold4.Rep1: alpha=0.88216, lambda=0.001899 
## + Fold4.Rep1: alpha=0.55337, lambda=2.737403 
## - Fold4.Rep1: alpha=0.55337, lambda=2.737403 
## + Fold4.Rep1: alpha=0.82978, lambda=0.154434 
## - Fold4.Rep1: alpha=0.82978, lambda=0.154434 
## + Fold4.Rep1: alpha=0.31549, lambda=7.029301 
## - Fold4.Rep1: alpha=0.31549, lambda=7.029301 
## + Fold4.Rep1: alpha=0.89748, lambda=0.020774 
## - Fold4.Rep1: alpha=0.89748, lambda=0.020774 
## + Fold4.Rep1: alpha=0.58332, lambda=0.008189 
## - Fold4.Rep1: alpha=0.58332, lambda=0.008189 
## + Fold4.Rep1: alpha=0.66370, lambda=0.005494 
## - Fold4.Rep1: alpha=0.66370, lambda=0.005494 
## + Fold4.Rep1: alpha=0.87945, lambda=0.008348 
## - Fold4.Rep1: alpha=0.87945, lambda=0.008348 
## + Fold4.Rep1: alpha=0.39224, lambda=4.100786 
## - Fold4.Rep1: alpha=0.39224, lambda=4.100786 
## + Fold4.Rep1: alpha=0.21126, lambda=3.394816 
## - Fold4.Rep1: alpha=0.21126, lambda=3.394816 
## + Fold4.Rep1: alpha=0.20867, lambda=1.714738 
## - Fold4.Rep1: alpha=0.20867, lambda=1.714738 
## + Fold4.Rep1: alpha=0.29287, lambda=0.465785 
## - Fold4.Rep1: alpha=0.29287, lambda=0.465785 
## + Fold4.Rep1: alpha=0.81856, lambda=0.021962 
## - Fold4.Rep1: alpha=0.81856, lambda=0.021962 
## + Fold4.Rep1: alpha=0.66803, lambda=6.064987 
## - Fold4.Rep1: alpha=0.66803, lambda=6.064987 
## + Fold4.Rep1: alpha=0.48714, lambda=0.971740 
## - Fold4.Rep1: alpha=0.48714, lambda=0.971740 
## + Fold4.Rep1: alpha=0.53708, lambda=0.217687 
## - Fold4.Rep1: alpha=0.53708, lambda=0.217687 
## + Fold5.Rep1: alpha=0.88673, lambda=0.188648 
## - Fold5.Rep1: alpha=0.88673, lambda=0.188648 
## + Fold5.Rep1: alpha=0.17251, lambda=0.149375 
## - Fold5.Rep1: alpha=0.17251, lambda=0.149375 
## + Fold5.Rep1: alpha=0.52333, lambda=0.072676 
## - Fold5.Rep1: alpha=0.52333, lambda=0.072676 
## + Fold5.Rep1: alpha=0.89036, lambda=3.971283 
## - Fold5.Rep1: alpha=0.89036, lambda=3.971283 
## + Fold5.Rep1: alpha=0.06876, lambda=0.113433 
## - Fold5.Rep1: alpha=0.06876, lambda=0.113433 
## + Fold5.Rep1: alpha=0.69652, lambda=0.001657 
## - Fold5.Rep1: alpha=0.69652, lambda=0.001657 
## + Fold5.Rep1: alpha=0.82268, lambda=1.898387 
## - Fold5.Rep1: alpha=0.82268, lambda=1.898387 
## + Fold5.Rep1: alpha=0.35681, lambda=0.001551 
## - Fold5.Rep1: alpha=0.35681, lambda=0.001551 
## + Fold5.Rep1: alpha=0.83235, lambda=2.524038 
## - Fold5.Rep1: alpha=0.83235, lambda=2.524038 
## + Fold5.Rep1: alpha=0.88216, lambda=0.001899 
## - Fold5.Rep1: alpha=0.88216, lambda=0.001899 
## + Fold5.Rep1: alpha=0.55337, lambda=2.737403 
## - Fold5.Rep1: alpha=0.55337, lambda=2.737403 
## + Fold5.Rep1: alpha=0.82978, lambda=0.154434 
## - Fold5.Rep1: alpha=0.82978, lambda=0.154434 
## + Fold5.Rep1: alpha=0.31549, lambda=7.029301 
## - Fold5.Rep1: alpha=0.31549, lambda=7.029301 
## + Fold5.Rep1: alpha=0.89748, lambda=0.020774 
## - Fold5.Rep1: alpha=0.89748, lambda=0.020774 
## + Fold5.Rep1: alpha=0.58332, lambda=0.008189 
## - Fold5.Rep1: alpha=0.58332, lambda=0.008189 
## + Fold5.Rep1: alpha=0.66370, lambda=0.005494 
## - Fold5.Rep1: alpha=0.66370, lambda=0.005494 
## + Fold5.Rep1: alpha=0.87945, lambda=0.008348 
## - Fold5.Rep1: alpha=0.87945, lambda=0.008348 
## + Fold5.Rep1: alpha=0.39224, lambda=4.100786 
## - Fold5.Rep1: alpha=0.39224, lambda=4.100786 
## + Fold5.Rep1: alpha=0.21126, lambda=3.394816 
## - Fold5.Rep1: alpha=0.21126, lambda=3.394816 
## + Fold5.Rep1: alpha=0.20867, lambda=1.714738 
## - Fold5.Rep1: alpha=0.20867, lambda=1.714738 
## + Fold5.Rep1: alpha=0.29287, lambda=0.465785 
## - Fold5.Rep1: alpha=0.29287, lambda=0.465785 
## + Fold5.Rep1: alpha=0.81856, lambda=0.021962 
## - Fold5.Rep1: alpha=0.81856, lambda=0.021962 
## + Fold5.Rep1: alpha=0.66803, lambda=6.064987 
## - Fold5.Rep1: alpha=0.66803, lambda=6.064987 
## + Fold5.Rep1: alpha=0.48714, lambda=0.971740 
## - Fold5.Rep1: alpha=0.48714, lambda=0.971740 
## + Fold5.Rep1: alpha=0.53708, lambda=0.217687 
## - Fold5.Rep1: alpha=0.53708, lambda=0.217687 
## + Fold1.Rep2: alpha=0.88673, lambda=0.188648 
## - Fold1.Rep2: alpha=0.88673, lambda=0.188648 
## + Fold1.Rep2: alpha=0.17251, lambda=0.149375 
## - Fold1.Rep2: alpha=0.17251, lambda=0.149375 
## + Fold1.Rep2: alpha=0.52333, lambda=0.072676 
## - Fold1.Rep2: alpha=0.52333, lambda=0.072676 
## + Fold1.Rep2: alpha=0.89036, lambda=3.971283 
## - Fold1.Rep2: alpha=0.89036, lambda=3.971283 
## + Fold1.Rep2: alpha=0.06876, lambda=0.113433 
## - Fold1.Rep2: alpha=0.06876, lambda=0.113433 
## + Fold1.Rep2: alpha=0.69652, lambda=0.001657 
## - Fold1.Rep2: alpha=0.69652, lambda=0.001657 
## + Fold1.Rep2: alpha=0.82268, lambda=1.898387 
## - Fold1.Rep2: alpha=0.82268, lambda=1.898387 
## + Fold1.Rep2: alpha=0.35681, lambda=0.001551 
## - Fold1.Rep2: alpha=0.35681, lambda=0.001551 
## + Fold1.Rep2: alpha=0.83235, lambda=2.524038 
## - Fold1.Rep2: alpha=0.83235, lambda=2.524038 
## + Fold1.Rep2: alpha=0.88216, lambda=0.001899 
## - Fold1.Rep2: alpha=0.88216, lambda=0.001899 
## + Fold1.Rep2: alpha=0.55337, lambda=2.737403 
## - Fold1.Rep2: alpha=0.55337, lambda=2.737403 
## + Fold1.Rep2: alpha=0.82978, lambda=0.154434 
## - Fold1.Rep2: alpha=0.82978, lambda=0.154434 
## + Fold1.Rep2: alpha=0.31549, lambda=7.029301 
## - Fold1.Rep2: alpha=0.31549, lambda=7.029301 
## + Fold1.Rep2: alpha=0.89748, lambda=0.020774 
## - Fold1.Rep2: alpha=0.89748, lambda=0.020774 
## + Fold1.Rep2: alpha=0.58332, lambda=0.008189 
## - Fold1.Rep2: alpha=0.58332, lambda=0.008189 
## + Fold1.Rep2: alpha=0.66370, lambda=0.005494 
## - Fold1.Rep2: alpha=0.66370, lambda=0.005494 
## + Fold1.Rep2: alpha=0.87945, lambda=0.008348 
## - Fold1.Rep2: alpha=0.87945, lambda=0.008348 
## + Fold1.Rep2: alpha=0.39224, lambda=4.100786 
## - Fold1.Rep2: alpha=0.39224, lambda=4.100786 
## + Fold1.Rep2: alpha=0.21126, lambda=3.394816 
## - Fold1.Rep2: alpha=0.21126, lambda=3.394816 
## + Fold1.Rep2: alpha=0.20867, lambda=1.714738 
## - Fold1.Rep2: alpha=0.20867, lambda=1.714738 
## + Fold1.Rep2: alpha=0.29287, lambda=0.465785 
## - Fold1.Rep2: alpha=0.29287, lambda=0.465785 
## + Fold1.Rep2: alpha=0.81856, lambda=0.021962 
## - Fold1.Rep2: alpha=0.81856, lambda=0.021962 
## + Fold1.Rep2: alpha=0.66803, lambda=6.064987 
## - Fold1.Rep2: alpha=0.66803, lambda=6.064987 
## + Fold1.Rep2: alpha=0.48714, lambda=0.971740 
## - Fold1.Rep2: alpha=0.48714, lambda=0.971740 
## + Fold1.Rep2: alpha=0.53708, lambda=0.217687 
## - Fold1.Rep2: alpha=0.53708, lambda=0.217687 
## + Fold2.Rep2: alpha=0.88673, lambda=0.188648 
## - Fold2.Rep2: alpha=0.88673, lambda=0.188648 
## + Fold2.Rep2: alpha=0.17251, lambda=0.149375 
## - Fold2.Rep2: alpha=0.17251, lambda=0.149375 
## + Fold2.Rep2: alpha=0.52333, lambda=0.072676 
## - Fold2.Rep2: alpha=0.52333, lambda=0.072676 
## + Fold2.Rep2: alpha=0.89036, lambda=3.971283 
## - Fold2.Rep2: alpha=0.89036, lambda=3.971283 
## + Fold2.Rep2: alpha=0.06876, lambda=0.113433 
## - Fold2.Rep2: alpha=0.06876, lambda=0.113433 
## + Fold2.Rep2: alpha=0.69652, lambda=0.001657 
## - Fold2.Rep2: alpha=0.69652, lambda=0.001657 
## + Fold2.Rep2: alpha=0.82268, lambda=1.898387 
## - Fold2.Rep2: alpha=0.82268, lambda=1.898387 
## + Fold2.Rep2: alpha=0.35681, lambda=0.001551 
## - Fold2.Rep2: alpha=0.35681, lambda=0.001551 
## + Fold2.Rep2: alpha=0.83235, lambda=2.524038 
## - Fold2.Rep2: alpha=0.83235, lambda=2.524038 
## + Fold2.Rep2: alpha=0.88216, lambda=0.001899 
## - Fold2.Rep2: alpha=0.88216, lambda=0.001899 
## + Fold2.Rep2: alpha=0.55337, lambda=2.737403 
## - Fold2.Rep2: alpha=0.55337, lambda=2.737403 
## + Fold2.Rep2: alpha=0.82978, lambda=0.154434 
## - Fold2.Rep2: alpha=0.82978, lambda=0.154434 
## + Fold2.Rep2: alpha=0.31549, lambda=7.029301 
## - Fold2.Rep2: alpha=0.31549, lambda=7.029301 
## + Fold2.Rep2: alpha=0.89748, lambda=0.020774 
## - Fold2.Rep2: alpha=0.89748, lambda=0.020774 
## + Fold2.Rep2: alpha=0.58332, lambda=0.008189 
## - Fold2.Rep2: alpha=0.58332, lambda=0.008189 
## + Fold2.Rep2: alpha=0.66370, lambda=0.005494 
## - Fold2.Rep2: alpha=0.66370, lambda=0.005494 
## + Fold2.Rep2: alpha=0.87945, lambda=0.008348 
## - Fold2.Rep2: alpha=0.87945, lambda=0.008348 
## + Fold2.Rep2: alpha=0.39224, lambda=4.100786 
## - Fold2.Rep2: alpha=0.39224, lambda=4.100786 
## + Fold2.Rep2: alpha=0.21126, lambda=3.394816 
## - Fold2.Rep2: alpha=0.21126, lambda=3.394816 
## + Fold2.Rep2: alpha=0.20867, lambda=1.714738 
## - Fold2.Rep2: alpha=0.20867, lambda=1.714738 
## + Fold2.Rep2: alpha=0.29287, lambda=0.465785 
## - Fold2.Rep2: alpha=0.29287, lambda=0.465785 
## + Fold2.Rep2: alpha=0.81856, lambda=0.021962 
## - Fold2.Rep2: alpha=0.81856, lambda=0.021962 
## + Fold2.Rep2: alpha=0.66803, lambda=6.064987 
## - Fold2.Rep2: alpha=0.66803, lambda=6.064987 
## + Fold2.Rep2: alpha=0.48714, lambda=0.971740 
## - Fold2.Rep2: alpha=0.48714, lambda=0.971740 
## + Fold2.Rep2: alpha=0.53708, lambda=0.217687 
## - Fold2.Rep2: alpha=0.53708, lambda=0.217687 
## + Fold3.Rep2: alpha=0.88673, lambda=0.188648 
## - Fold3.Rep2: alpha=0.88673, lambda=0.188648 
## + Fold3.Rep2: alpha=0.17251, lambda=0.149375 
## - Fold3.Rep2: alpha=0.17251, lambda=0.149375 
## + Fold3.Rep2: alpha=0.52333, lambda=0.072676 
## - Fold3.Rep2: alpha=0.52333, lambda=0.072676 
## + Fold3.Rep2: alpha=0.89036, lambda=3.971283 
## - Fold3.Rep2: alpha=0.89036, lambda=3.971283 
## + Fold3.Rep2: alpha=0.06876, lambda=0.113433 
## - Fold3.Rep2: alpha=0.06876, lambda=0.113433 
## + Fold3.Rep2: alpha=0.69652, lambda=0.001657 
## - Fold3.Rep2: alpha=0.69652, lambda=0.001657 
## + Fold3.Rep2: alpha=0.82268, lambda=1.898387 
## - Fold3.Rep2: alpha=0.82268, lambda=1.898387 
## + Fold3.Rep2: alpha=0.35681, lambda=0.001551 
## - Fold3.Rep2: alpha=0.35681, lambda=0.001551 
## + Fold3.Rep2: alpha=0.83235, lambda=2.524038 
## - Fold3.Rep2: alpha=0.83235, lambda=2.524038 
## + Fold3.Rep2: alpha=0.88216, lambda=0.001899 
## - Fold3.Rep2: alpha=0.88216, lambda=0.001899 
## + Fold3.Rep2: alpha=0.55337, lambda=2.737403 
## - Fold3.Rep2: alpha=0.55337, lambda=2.737403 
## + Fold3.Rep2: alpha=0.82978, lambda=0.154434 
## - Fold3.Rep2: alpha=0.82978, lambda=0.154434 
## + Fold3.Rep2: alpha=0.31549, lambda=7.029301 
## - Fold3.Rep2: alpha=0.31549, lambda=7.029301 
## + Fold3.Rep2: alpha=0.89748, lambda=0.020774 
## - Fold3.Rep2: alpha=0.89748, lambda=0.020774 
## + Fold3.Rep2: alpha=0.58332, lambda=0.008189 
## - Fold3.Rep2: alpha=0.58332, lambda=0.008189 
## + Fold3.Rep2: alpha=0.66370, lambda=0.005494 
## - Fold3.Rep2: alpha=0.66370, lambda=0.005494 
## + Fold3.Rep2: alpha=0.87945, lambda=0.008348 
## - Fold3.Rep2: alpha=0.87945, lambda=0.008348 
## + Fold3.Rep2: alpha=0.39224, lambda=4.100786 
## - Fold3.Rep2: alpha=0.39224, lambda=4.100786 
## + Fold3.Rep2: alpha=0.21126, lambda=3.394816 
## - Fold3.Rep2: alpha=0.21126, lambda=3.394816 
## + Fold3.Rep2: alpha=0.20867, lambda=1.714738 
## - Fold3.Rep2: alpha=0.20867, lambda=1.714738 
## + Fold3.Rep2: alpha=0.29287, lambda=0.465785 
## - Fold3.Rep2: alpha=0.29287, lambda=0.465785 
## + Fold3.Rep2: alpha=0.81856, lambda=0.021962 
## - Fold3.Rep2: alpha=0.81856, lambda=0.021962 
## + Fold3.Rep2: alpha=0.66803, lambda=6.064987 
## - Fold3.Rep2: alpha=0.66803, lambda=6.064987 
## + Fold3.Rep2: alpha=0.48714, lambda=0.971740 
## - Fold3.Rep2: alpha=0.48714, lambda=0.971740 
## + Fold3.Rep2: alpha=0.53708, lambda=0.217687 
## - Fold3.Rep2: alpha=0.53708, lambda=0.217687 
## + Fold4.Rep2: alpha=0.88673, lambda=0.188648 
## - Fold4.Rep2: alpha=0.88673, lambda=0.188648 
## + Fold4.Rep2: alpha=0.17251, lambda=0.149375 
## - Fold4.Rep2: alpha=0.17251, lambda=0.149375 
## + Fold4.Rep2: alpha=0.52333, lambda=0.072676 
## - Fold4.Rep2: alpha=0.52333, lambda=0.072676 
## + Fold4.Rep2: alpha=0.89036, lambda=3.971283 
## - Fold4.Rep2: alpha=0.89036, lambda=3.971283 
## + Fold4.Rep2: alpha=0.06876, lambda=0.113433 
## - Fold4.Rep2: alpha=0.06876, lambda=0.113433 
## + Fold4.Rep2: alpha=0.69652, lambda=0.001657 
## - Fold4.Rep2: alpha=0.69652, lambda=0.001657 
## + Fold4.Rep2: alpha=0.82268, lambda=1.898387 
## - Fold4.Rep2: alpha=0.82268, lambda=1.898387 
## + Fold4.Rep2: alpha=0.35681, lambda=0.001551 
## - Fold4.Rep2: alpha=0.35681, lambda=0.001551 
## + Fold4.Rep2: alpha=0.83235, lambda=2.524038 
## - Fold4.Rep2: alpha=0.83235, lambda=2.524038 
## + Fold4.Rep2: alpha=0.88216, lambda=0.001899 
## - Fold4.Rep2: alpha=0.88216, lambda=0.001899 
## + Fold4.Rep2: alpha=0.55337, lambda=2.737403 
## - Fold4.Rep2: alpha=0.55337, lambda=2.737403 
## + Fold4.Rep2: alpha=0.82978, lambda=0.154434 
## - Fold4.Rep2: alpha=0.82978, lambda=0.154434 
## + Fold4.Rep2: alpha=0.31549, lambda=7.029301 
## - Fold4.Rep2: alpha=0.31549, lambda=7.029301 
## + Fold4.Rep2: alpha=0.89748, lambda=0.020774 
## - Fold4.Rep2: alpha=0.89748, lambda=0.020774 
## + Fold4.Rep2: alpha=0.58332, lambda=0.008189 
## - Fold4.Rep2: alpha=0.58332, lambda=0.008189 
## + Fold4.Rep2: alpha=0.66370, lambda=0.005494 
## - Fold4.Rep2: alpha=0.66370, lambda=0.005494 
## + Fold4.Rep2: alpha=0.87945, lambda=0.008348 
## - Fold4.Rep2: alpha=0.87945, lambda=0.008348 
## + Fold4.Rep2: alpha=0.39224, lambda=4.100786 
## - Fold4.Rep2: alpha=0.39224, lambda=4.100786 
## + Fold4.Rep2: alpha=0.21126, lambda=3.394816 
## - Fold4.Rep2: alpha=0.21126, lambda=3.394816 
## + Fold4.Rep2: alpha=0.20867, lambda=1.714738 
## - Fold4.Rep2: alpha=0.20867, lambda=1.714738 
## + Fold4.Rep2: alpha=0.29287, lambda=0.465785 
## - Fold4.Rep2: alpha=0.29287, lambda=0.465785 
## + Fold4.Rep2: alpha=0.81856, lambda=0.021962 
## - Fold4.Rep2: alpha=0.81856, lambda=0.021962 
## + Fold4.Rep2: alpha=0.66803, lambda=6.064987 
## - Fold4.Rep2: alpha=0.66803, lambda=6.064987 
## + Fold4.Rep2: alpha=0.48714, lambda=0.971740 
## - Fold4.Rep2: alpha=0.48714, lambda=0.971740 
## + Fold4.Rep2: alpha=0.53708, lambda=0.217687 
## - Fold4.Rep2: alpha=0.53708, lambda=0.217687 
## + Fold5.Rep2: alpha=0.88673, lambda=0.188648 
## - Fold5.Rep2: alpha=0.88673, lambda=0.188648 
## + Fold5.Rep2: alpha=0.17251, lambda=0.149375 
## - Fold5.Rep2: alpha=0.17251, lambda=0.149375 
## + Fold5.Rep2: alpha=0.52333, lambda=0.072676 
## - Fold5.Rep2: alpha=0.52333, lambda=0.072676 
## + Fold5.Rep2: alpha=0.89036, lambda=3.971283 
## - Fold5.Rep2: alpha=0.89036, lambda=3.971283 
## + Fold5.Rep2: alpha=0.06876, lambda=0.113433 
## - Fold5.Rep2: alpha=0.06876, lambda=0.113433 
## + Fold5.Rep2: alpha=0.69652, lambda=0.001657 
## - Fold5.Rep2: alpha=0.69652, lambda=0.001657 
## + Fold5.Rep2: alpha=0.82268, lambda=1.898387 
## - Fold5.Rep2: alpha=0.82268, lambda=1.898387 
## + Fold5.Rep2: alpha=0.35681, lambda=0.001551 
## - Fold5.Rep2: alpha=0.35681, lambda=0.001551 
## + Fold5.Rep2: alpha=0.83235, lambda=2.524038 
## - Fold5.Rep2: alpha=0.83235, lambda=2.524038 
## + Fold5.Rep2: alpha=0.88216, lambda=0.001899 
## - Fold5.Rep2: alpha=0.88216, lambda=0.001899 
## + Fold5.Rep2: alpha=0.55337, lambda=2.737403 
## - Fold5.Rep2: alpha=0.55337, lambda=2.737403 
## + Fold5.Rep2: alpha=0.82978, lambda=0.154434 
## - Fold5.Rep2: alpha=0.82978, lambda=0.154434 
## + Fold5.Rep2: alpha=0.31549, lambda=7.029301 
## - Fold5.Rep2: alpha=0.31549, lambda=7.029301 
## + Fold5.Rep2: alpha=0.89748, lambda=0.020774 
## - Fold5.Rep2: alpha=0.89748, lambda=0.020774 
## + Fold5.Rep2: alpha=0.58332, lambda=0.008189 
## - Fold5.Rep2: alpha=0.58332, lambda=0.008189 
## + Fold5.Rep2: alpha=0.66370, lambda=0.005494 
## - Fold5.Rep2: alpha=0.66370, lambda=0.005494 
## + Fold5.Rep2: alpha=0.87945, lambda=0.008348 
## - Fold5.Rep2: alpha=0.87945, lambda=0.008348 
## + Fold5.Rep2: alpha=0.39224, lambda=4.100786 
## - Fold5.Rep2: alpha=0.39224, lambda=4.100786 
## + Fold5.Rep2: alpha=0.21126, lambda=3.394816 
## - Fold5.Rep2: alpha=0.21126, lambda=3.394816 
## + Fold5.Rep2: alpha=0.20867, lambda=1.714738 
## - Fold5.Rep2: alpha=0.20867, lambda=1.714738 
## + Fold5.Rep2: alpha=0.29287, lambda=0.465785 
## - Fold5.Rep2: alpha=0.29287, lambda=0.465785 
## + Fold5.Rep2: alpha=0.81856, lambda=0.021962 
## - Fold5.Rep2: alpha=0.81856, lambda=0.021962 
## + Fold5.Rep2: alpha=0.66803, lambda=6.064987 
## - Fold5.Rep2: alpha=0.66803, lambda=6.064987 
## + Fold5.Rep2: alpha=0.48714, lambda=0.971740 
## - Fold5.Rep2: alpha=0.48714, lambda=0.971740 
## + Fold5.Rep2: alpha=0.53708, lambda=0.217687 
## - Fold5.Rep2: alpha=0.53708, lambda=0.217687 
## + Fold1.Rep3: alpha=0.88673, lambda=0.188648 
## - Fold1.Rep3: alpha=0.88673, lambda=0.188648 
## + Fold1.Rep3: alpha=0.17251, lambda=0.149375 
## - Fold1.Rep3: alpha=0.17251, lambda=0.149375 
## + Fold1.Rep3: alpha=0.52333, lambda=0.072676 
## - Fold1.Rep3: alpha=0.52333, lambda=0.072676 
## + Fold1.Rep3: alpha=0.89036, lambda=3.971283 
## - Fold1.Rep3: alpha=0.89036, lambda=3.971283 
## + Fold1.Rep3: alpha=0.06876, lambda=0.113433 
## - Fold1.Rep3: alpha=0.06876, lambda=0.113433 
## + Fold1.Rep3: alpha=0.69652, lambda=0.001657 
## - Fold1.Rep3: alpha=0.69652, lambda=0.001657 
## + Fold1.Rep3: alpha=0.82268, lambda=1.898387 
## - Fold1.Rep3: alpha=0.82268, lambda=1.898387 
## + Fold1.Rep3: alpha=0.35681, lambda=0.001551 
## - Fold1.Rep3: alpha=0.35681, lambda=0.001551 
## + Fold1.Rep3: alpha=0.83235, lambda=2.524038 
## - Fold1.Rep3: alpha=0.83235, lambda=2.524038 
## + Fold1.Rep3: alpha=0.88216, lambda=0.001899 
## - Fold1.Rep3: alpha=0.88216, lambda=0.001899 
## + Fold1.Rep3: alpha=0.55337, lambda=2.737403 
## - Fold1.Rep3: alpha=0.55337, lambda=2.737403 
## + Fold1.Rep3: alpha=0.82978, lambda=0.154434 
## - Fold1.Rep3: alpha=0.82978, lambda=0.154434 
## + Fold1.Rep3: alpha=0.31549, lambda=7.029301 
## - Fold1.Rep3: alpha=0.31549, lambda=7.029301 
## + Fold1.Rep3: alpha=0.89748, lambda=0.020774 
## - Fold1.Rep3: alpha=0.89748, lambda=0.020774 
## + Fold1.Rep3: alpha=0.58332, lambda=0.008189 
## - Fold1.Rep3: alpha=0.58332, lambda=0.008189 
## + Fold1.Rep3: alpha=0.66370, lambda=0.005494 
## - Fold1.Rep3: alpha=0.66370, lambda=0.005494 
## + Fold1.Rep3: alpha=0.87945, lambda=0.008348 
## - Fold1.Rep3: alpha=0.87945, lambda=0.008348 
## + Fold1.Rep3: alpha=0.39224, lambda=4.100786 
## - Fold1.Rep3: alpha=0.39224, lambda=4.100786 
## + Fold1.Rep3: alpha=0.21126, lambda=3.394816 
## - Fold1.Rep3: alpha=0.21126, lambda=3.394816 
## + Fold1.Rep3: alpha=0.20867, lambda=1.714738 
## - Fold1.Rep3: alpha=0.20867, lambda=1.714738 
## + Fold1.Rep3: alpha=0.29287, lambda=0.465785 
## - Fold1.Rep3: alpha=0.29287, lambda=0.465785 
## + Fold1.Rep3: alpha=0.81856, lambda=0.021962 
## - Fold1.Rep3: alpha=0.81856, lambda=0.021962 
## + Fold1.Rep3: alpha=0.66803, lambda=6.064987 
## - Fold1.Rep3: alpha=0.66803, lambda=6.064987 
## + Fold1.Rep3: alpha=0.48714, lambda=0.971740 
## - Fold1.Rep3: alpha=0.48714, lambda=0.971740 
## + Fold1.Rep3: alpha=0.53708, lambda=0.217687 
## - Fold1.Rep3: alpha=0.53708, lambda=0.217687 
## + Fold2.Rep3: alpha=0.88673, lambda=0.188648 
## - Fold2.Rep3: alpha=0.88673, lambda=0.188648 
## + Fold2.Rep3: alpha=0.17251, lambda=0.149375 
## - Fold2.Rep3: alpha=0.17251, lambda=0.149375 
## + Fold2.Rep3: alpha=0.52333, lambda=0.072676 
## - Fold2.Rep3: alpha=0.52333, lambda=0.072676 
## + Fold2.Rep3: alpha=0.89036, lambda=3.971283 
## - Fold2.Rep3: alpha=0.89036, lambda=3.971283 
## + Fold2.Rep3: alpha=0.06876, lambda=0.113433 
## - Fold2.Rep3: alpha=0.06876, lambda=0.113433 
## + Fold2.Rep3: alpha=0.69652, lambda=0.001657 
## - Fold2.Rep3: alpha=0.69652, lambda=0.001657 
## + Fold2.Rep3: alpha=0.82268, lambda=1.898387 
## - Fold2.Rep3: alpha=0.82268, lambda=1.898387 
## + Fold2.Rep3: alpha=0.35681, lambda=0.001551 
## - Fold2.Rep3: alpha=0.35681, lambda=0.001551 
## + Fold2.Rep3: alpha=0.83235, lambda=2.524038 
## - Fold2.Rep3: alpha=0.83235, lambda=2.524038 
## + Fold2.Rep3: alpha=0.88216, lambda=0.001899 
## - Fold2.Rep3: alpha=0.88216, lambda=0.001899 
## + Fold2.Rep3: alpha=0.55337, lambda=2.737403 
## - Fold2.Rep3: alpha=0.55337, lambda=2.737403 
## + Fold2.Rep3: alpha=0.82978, lambda=0.154434 
## - Fold2.Rep3: alpha=0.82978, lambda=0.154434 
## + Fold2.Rep3: alpha=0.31549, lambda=7.029301 
## - Fold2.Rep3: alpha=0.31549, lambda=7.029301 
## + Fold2.Rep3: alpha=0.89748, lambda=0.020774 
## - Fold2.Rep3: alpha=0.89748, lambda=0.020774 
## + Fold2.Rep3: alpha=0.58332, lambda=0.008189 
## - Fold2.Rep3: alpha=0.58332, lambda=0.008189 
## + Fold2.Rep3: alpha=0.66370, lambda=0.005494 
## - Fold2.Rep3: alpha=0.66370, lambda=0.005494 
## + Fold2.Rep3: alpha=0.87945, lambda=0.008348 
## - Fold2.Rep3: alpha=0.87945, lambda=0.008348 
## + Fold2.Rep3: alpha=0.39224, lambda=4.100786 
## - Fold2.Rep3: alpha=0.39224, lambda=4.100786 
## + Fold2.Rep3: alpha=0.21126, lambda=3.394816 
## - Fold2.Rep3: alpha=0.21126, lambda=3.394816 
## + Fold2.Rep3: alpha=0.20867, lambda=1.714738 
## - Fold2.Rep3: alpha=0.20867, lambda=1.714738 
## + Fold2.Rep3: alpha=0.29287, lambda=0.465785 
## - Fold2.Rep3: alpha=0.29287, lambda=0.465785 
## + Fold2.Rep3: alpha=0.81856, lambda=0.021962 
## - Fold2.Rep3: alpha=0.81856, lambda=0.021962 
## + Fold2.Rep3: alpha=0.66803, lambda=6.064987 
## - Fold2.Rep3: alpha=0.66803, lambda=6.064987 
## + Fold2.Rep3: alpha=0.48714, lambda=0.971740 
## - Fold2.Rep3: alpha=0.48714, lambda=0.971740 
## + Fold2.Rep3: alpha=0.53708, lambda=0.217687 
## - Fold2.Rep3: alpha=0.53708, lambda=0.217687 
## + Fold3.Rep3: alpha=0.88673, lambda=0.188648 
## - Fold3.Rep3: alpha=0.88673, lambda=0.188648 
## + Fold3.Rep3: alpha=0.17251, lambda=0.149375 
## - Fold3.Rep3: alpha=0.17251, lambda=0.149375 
## + Fold3.Rep3: alpha=0.52333, lambda=0.072676 
## - Fold3.Rep3: alpha=0.52333, lambda=0.072676 
## + Fold3.Rep3: alpha=0.89036, lambda=3.971283 
## - Fold3.Rep3: alpha=0.89036, lambda=3.971283 
## + Fold3.Rep3: alpha=0.06876, lambda=0.113433 
## - Fold3.Rep3: alpha=0.06876, lambda=0.113433 
## + Fold3.Rep3: alpha=0.69652, lambda=0.001657 
## - Fold3.Rep3: alpha=0.69652, lambda=0.001657 
## + Fold3.Rep3: alpha=0.82268, lambda=1.898387 
## - Fold3.Rep3: alpha=0.82268, lambda=1.898387 
## + Fold3.Rep3: alpha=0.35681, lambda=0.001551 
## - Fold3.Rep3: alpha=0.35681, lambda=0.001551 
## + Fold3.Rep3: alpha=0.83235, lambda=2.524038 
## - Fold3.Rep3: alpha=0.83235, lambda=2.524038 
## + Fold3.Rep3: alpha=0.88216, lambda=0.001899 
## - Fold3.Rep3: alpha=0.88216, lambda=0.001899 
## + Fold3.Rep3: alpha=0.55337, lambda=2.737403 
## - Fold3.Rep3: alpha=0.55337, lambda=2.737403 
## + Fold3.Rep3: alpha=0.82978, lambda=0.154434 
## - Fold3.Rep3: alpha=0.82978, lambda=0.154434 
## + Fold3.Rep3: alpha=0.31549, lambda=7.029301 
## - Fold3.Rep3: alpha=0.31549, lambda=7.029301 
## + Fold3.Rep3: alpha=0.89748, lambda=0.020774 
## - Fold3.Rep3: alpha=0.89748, lambda=0.020774 
## + Fold3.Rep3: alpha=0.58332, lambda=0.008189 
## - Fold3.Rep3: alpha=0.58332, lambda=0.008189 
## + Fold3.Rep3: alpha=0.66370, lambda=0.005494 
## - Fold3.Rep3: alpha=0.66370, lambda=0.005494 
## + Fold3.Rep3: alpha=0.87945, lambda=0.008348 
## - Fold3.Rep3: alpha=0.87945, lambda=0.008348 
## + Fold3.Rep3: alpha=0.39224, lambda=4.100786 
## - Fold3.Rep3: alpha=0.39224, lambda=4.100786 
## + Fold3.Rep3: alpha=0.21126, lambda=3.394816 
## - Fold3.Rep3: alpha=0.21126, lambda=3.394816 
## + Fold3.Rep3: alpha=0.20867, lambda=1.714738 
## - Fold3.Rep3: alpha=0.20867, lambda=1.714738 
## + Fold3.Rep3: alpha=0.29287, lambda=0.465785 
## - Fold3.Rep3: alpha=0.29287, lambda=0.465785 
## + Fold3.Rep3: alpha=0.81856, lambda=0.021962 
## - Fold3.Rep3: alpha=0.81856, lambda=0.021962 
## + Fold3.Rep3: alpha=0.66803, lambda=6.064987 
## - Fold3.Rep3: alpha=0.66803, lambda=6.064987 
## + Fold3.Rep3: alpha=0.48714, lambda=0.971740 
## - Fold3.Rep3: alpha=0.48714, lambda=0.971740 
## + Fold3.Rep3: alpha=0.53708, lambda=0.217687 
## - Fold3.Rep3: alpha=0.53708, lambda=0.217687 
## + Fold4.Rep3: alpha=0.88673, lambda=0.188648 
## - Fold4.Rep3: alpha=0.88673, lambda=0.188648 
## + Fold4.Rep3: alpha=0.17251, lambda=0.149375 
## - Fold4.Rep3: alpha=0.17251, lambda=0.149375 
## + Fold4.Rep3: alpha=0.52333, lambda=0.072676 
## - Fold4.Rep3: alpha=0.52333, lambda=0.072676 
## + Fold4.Rep3: alpha=0.89036, lambda=3.971283 
## - Fold4.Rep3: alpha=0.89036, lambda=3.971283 
## + Fold4.Rep3: alpha=0.06876, lambda=0.113433 
## - Fold4.Rep3: alpha=0.06876, lambda=0.113433 
## + Fold4.Rep3: alpha=0.69652, lambda=0.001657 
## - Fold4.Rep3: alpha=0.69652, lambda=0.001657 
## + Fold4.Rep3: alpha=0.82268, lambda=1.898387 
## - Fold4.Rep3: alpha=0.82268, lambda=1.898387 
## + Fold4.Rep3: alpha=0.35681, lambda=0.001551 
## - Fold4.Rep3: alpha=0.35681, lambda=0.001551 
## + Fold4.Rep3: alpha=0.83235, lambda=2.524038 
## - Fold4.Rep3: alpha=0.83235, lambda=2.524038 
## + Fold4.Rep3: alpha=0.88216, lambda=0.001899 
## - Fold4.Rep3: alpha=0.88216, lambda=0.001899 
## + Fold4.Rep3: alpha=0.55337, lambda=2.737403 
## - Fold4.Rep3: alpha=0.55337, lambda=2.737403 
## + Fold4.Rep3: alpha=0.82978, lambda=0.154434 
## - Fold4.Rep3: alpha=0.82978, lambda=0.154434 
## + Fold4.Rep3: alpha=0.31549, lambda=7.029301 
## - Fold4.Rep3: alpha=0.31549, lambda=7.029301 
## + Fold4.Rep3: alpha=0.89748, lambda=0.020774 
## - Fold4.Rep3: alpha=0.89748, lambda=0.020774 
## + Fold4.Rep3: alpha=0.58332, lambda=0.008189 
## - Fold4.Rep3: alpha=0.58332, lambda=0.008189 
## + Fold4.Rep3: alpha=0.66370, lambda=0.005494 
## - Fold4.Rep3: alpha=0.66370, lambda=0.005494 
## + Fold4.Rep3: alpha=0.87945, lambda=0.008348 
## - Fold4.Rep3: alpha=0.87945, lambda=0.008348 
## + Fold4.Rep3: alpha=0.39224, lambda=4.100786 
## - Fold4.Rep3: alpha=0.39224, lambda=4.100786 
## + Fold4.Rep3: alpha=0.21126, lambda=3.394816 
## - Fold4.Rep3: alpha=0.21126, lambda=3.394816 
## + Fold4.Rep3: alpha=0.20867, lambda=1.714738 
## - Fold4.Rep3: alpha=0.20867, lambda=1.714738 
## + Fold4.Rep3: alpha=0.29287, lambda=0.465785 
## - Fold4.Rep3: alpha=0.29287, lambda=0.465785 
## + Fold4.Rep3: alpha=0.81856, lambda=0.021962 
## - Fold4.Rep3: alpha=0.81856, lambda=0.021962 
## + Fold4.Rep3: alpha=0.66803, lambda=6.064987 
## - Fold4.Rep3: alpha=0.66803, lambda=6.064987 
## + Fold4.Rep3: alpha=0.48714, lambda=0.971740 
## - Fold4.Rep3: alpha=0.48714, lambda=0.971740 
## + Fold4.Rep3: alpha=0.53708, lambda=0.217687 
## - Fold4.Rep3: alpha=0.53708, lambda=0.217687 
## + Fold5.Rep3: alpha=0.88673, lambda=0.188648 
## - Fold5.Rep3: alpha=0.88673, lambda=0.188648 
## + Fold5.Rep3: alpha=0.17251, lambda=0.149375 
## - Fold5.Rep3: alpha=0.17251, lambda=0.149375 
## + Fold5.Rep3: alpha=0.52333, lambda=0.072676 
## - Fold5.Rep3: alpha=0.52333, lambda=0.072676 
## + Fold5.Rep3: alpha=0.89036, lambda=3.971283 
## - Fold5.Rep3: alpha=0.89036, lambda=3.971283 
## + Fold5.Rep3: alpha=0.06876, lambda=0.113433 
## - Fold5.Rep3: alpha=0.06876, lambda=0.113433 
## + Fold5.Rep3: alpha=0.69652, lambda=0.001657 
## - Fold5.Rep3: alpha=0.69652, lambda=0.001657 
## + Fold5.Rep3: alpha=0.82268, lambda=1.898387 
## - Fold5.Rep3: alpha=0.82268, lambda=1.898387 
## + Fold5.Rep3: alpha=0.35681, lambda=0.001551 
## - Fold5.Rep3: alpha=0.35681, lambda=0.001551 
## + Fold5.Rep3: alpha=0.83235, lambda=2.524038 
## - Fold5.Rep3: alpha=0.83235, lambda=2.524038 
## + Fold5.Rep3: alpha=0.88216, lambda=0.001899 
## - Fold5.Rep3: alpha=0.88216, lambda=0.001899 
## + Fold5.Rep3: alpha=0.55337, lambda=2.737403 
## - Fold5.Rep3: alpha=0.55337, lambda=2.737403 
## + Fold5.Rep3: alpha=0.82978, lambda=0.154434 
## - Fold5.Rep3: alpha=0.82978, lambda=0.154434 
## + Fold5.Rep3: alpha=0.31549, lambda=7.029301 
## - Fold5.Rep3: alpha=0.31549, lambda=7.029301 
## + Fold5.Rep3: alpha=0.89748, lambda=0.020774 
## - Fold5.Rep3: alpha=0.89748, lambda=0.020774 
## + Fold5.Rep3: alpha=0.58332, lambda=0.008189 
## - Fold5.Rep3: alpha=0.58332, lambda=0.008189 
## + Fold5.Rep3: alpha=0.66370, lambda=0.005494 
## - Fold5.Rep3: alpha=0.66370, lambda=0.005494 
## + Fold5.Rep3: alpha=0.87945, lambda=0.008348 
## - Fold5.Rep3: alpha=0.87945, lambda=0.008348 
## + Fold5.Rep3: alpha=0.39224, lambda=4.100786 
## - Fold5.Rep3: alpha=0.39224, lambda=4.100786 
## + Fold5.Rep3: alpha=0.21126, lambda=3.394816 
## - Fold5.Rep3: alpha=0.21126, lambda=3.394816 
## + Fold5.Rep3: alpha=0.20867, lambda=1.714738 
## - Fold5.Rep3: alpha=0.20867, lambda=1.714738 
## + Fold5.Rep3: alpha=0.29287, lambda=0.465785 
## - Fold5.Rep3: alpha=0.29287, lambda=0.465785 
## + Fold5.Rep3: alpha=0.81856, lambda=0.021962 
## - Fold5.Rep3: alpha=0.81856, lambda=0.021962 
## + Fold5.Rep3: alpha=0.66803, lambda=6.064987 
## - Fold5.Rep3: alpha=0.66803, lambda=6.064987 
## + Fold5.Rep3: alpha=0.48714, lambda=0.971740 
## - Fold5.Rep3: alpha=0.48714, lambda=0.971740 
## + Fold5.Rep3: alpha=0.53708, lambda=0.217687 
## - Fold5.Rep3: alpha=0.53708, lambda=0.217687 
## + Fold1.Rep4: alpha=0.88673, lambda=0.188648 
## - Fold1.Rep4: alpha=0.88673, lambda=0.188648 
## + Fold1.Rep4: alpha=0.17251, lambda=0.149375 
## - Fold1.Rep4: alpha=0.17251, lambda=0.149375 
## + Fold1.Rep4: alpha=0.52333, lambda=0.072676 
## - Fold1.Rep4: alpha=0.52333, lambda=0.072676 
## + Fold1.Rep4: alpha=0.89036, lambda=3.971283 
## - Fold1.Rep4: alpha=0.89036, lambda=3.971283 
## + Fold1.Rep4: alpha=0.06876, lambda=0.113433 
## - Fold1.Rep4: alpha=0.06876, lambda=0.113433 
## + Fold1.Rep4: alpha=0.69652, lambda=0.001657 
## - Fold1.Rep4: alpha=0.69652, lambda=0.001657 
## + Fold1.Rep4: alpha=0.82268, lambda=1.898387 
## - Fold1.Rep4: alpha=0.82268, lambda=1.898387 
## + Fold1.Rep4: alpha=0.35681, lambda=0.001551 
## - Fold1.Rep4: alpha=0.35681, lambda=0.001551 
## + Fold1.Rep4: alpha=0.83235, lambda=2.524038 
## - Fold1.Rep4: alpha=0.83235, lambda=2.524038 
## + Fold1.Rep4: alpha=0.88216, lambda=0.001899 
## - Fold1.Rep4: alpha=0.88216, lambda=0.001899 
## + Fold1.Rep4: alpha=0.55337, lambda=2.737403 
## - Fold1.Rep4: alpha=0.55337, lambda=2.737403 
## + Fold1.Rep4: alpha=0.82978, lambda=0.154434 
## - Fold1.Rep4: alpha=0.82978, lambda=0.154434 
## + Fold1.Rep4: alpha=0.31549, lambda=7.029301 
## - Fold1.Rep4: alpha=0.31549, lambda=7.029301 
## + Fold1.Rep4: alpha=0.89748, lambda=0.020774 
## - Fold1.Rep4: alpha=0.89748, lambda=0.020774 
## + Fold1.Rep4: alpha=0.58332, lambda=0.008189 
## - Fold1.Rep4: alpha=0.58332, lambda=0.008189 
## + Fold1.Rep4: alpha=0.66370, lambda=0.005494 
## - Fold1.Rep4: alpha=0.66370, lambda=0.005494 
## + Fold1.Rep4: alpha=0.87945, lambda=0.008348 
## - Fold1.Rep4: alpha=0.87945, lambda=0.008348 
## + Fold1.Rep4: alpha=0.39224, lambda=4.100786 
## - Fold1.Rep4: alpha=0.39224, lambda=4.100786 
## + Fold1.Rep4: alpha=0.21126, lambda=3.394816 
## - Fold1.Rep4: alpha=0.21126, lambda=3.394816 
## + Fold1.Rep4: alpha=0.20867, lambda=1.714738 
## - Fold1.Rep4: alpha=0.20867, lambda=1.714738 
## + Fold1.Rep4: alpha=0.29287, lambda=0.465785 
## - Fold1.Rep4: alpha=0.29287, lambda=0.465785 
## + Fold1.Rep4: alpha=0.81856, lambda=0.021962 
## - Fold1.Rep4: alpha=0.81856, lambda=0.021962 
## + Fold1.Rep4: alpha=0.66803, lambda=6.064987 
## - Fold1.Rep4: alpha=0.66803, lambda=6.064987 
## + Fold1.Rep4: alpha=0.48714, lambda=0.971740 
## - Fold1.Rep4: alpha=0.48714, lambda=0.971740 
## + Fold1.Rep4: alpha=0.53708, lambda=0.217687 
## - Fold1.Rep4: alpha=0.53708, lambda=0.217687 
## + Fold2.Rep4: alpha=0.88673, lambda=0.188648 
## - Fold2.Rep4: alpha=0.88673, lambda=0.188648 
## + Fold2.Rep4: alpha=0.17251, lambda=0.149375 
## - Fold2.Rep4: alpha=0.17251, lambda=0.149375 
## + Fold2.Rep4: alpha=0.52333, lambda=0.072676 
## - Fold2.Rep4: alpha=0.52333, lambda=0.072676 
## + Fold2.Rep4: alpha=0.89036, lambda=3.971283 
## - Fold2.Rep4: alpha=0.89036, lambda=3.971283 
## + Fold2.Rep4: alpha=0.06876, lambda=0.113433 
## - Fold2.Rep4: alpha=0.06876, lambda=0.113433 
## + Fold2.Rep4: alpha=0.69652, lambda=0.001657 
## - Fold2.Rep4: alpha=0.69652, lambda=0.001657 
## + Fold2.Rep4: alpha=0.82268, lambda=1.898387 
## - Fold2.Rep4: alpha=0.82268, lambda=1.898387 
## + Fold2.Rep4: alpha=0.35681, lambda=0.001551 
## - Fold2.Rep4: alpha=0.35681, lambda=0.001551 
## + Fold2.Rep4: alpha=0.83235, lambda=2.524038 
## - Fold2.Rep4: alpha=0.83235, lambda=2.524038 
## + Fold2.Rep4: alpha=0.88216, lambda=0.001899 
## - Fold2.Rep4: alpha=0.88216, lambda=0.001899 
## + Fold2.Rep4: alpha=0.55337, lambda=2.737403 
## - Fold2.Rep4: alpha=0.55337, lambda=2.737403 
## + Fold2.Rep4: alpha=0.82978, lambda=0.154434 
## - Fold2.Rep4: alpha=0.82978, lambda=0.154434 
## + Fold2.Rep4: alpha=0.31549, lambda=7.029301 
## - Fold2.Rep4: alpha=0.31549, lambda=7.029301 
## + Fold2.Rep4: alpha=0.89748, lambda=0.020774 
## - Fold2.Rep4: alpha=0.89748, lambda=0.020774 
## + Fold2.Rep4: alpha=0.58332, lambda=0.008189 
## - Fold2.Rep4: alpha=0.58332, lambda=0.008189 
## + Fold2.Rep4: alpha=0.66370, lambda=0.005494 
## - Fold2.Rep4: alpha=0.66370, lambda=0.005494 
## + Fold2.Rep4: alpha=0.87945, lambda=0.008348 
## - Fold2.Rep4: alpha=0.87945, lambda=0.008348 
## + Fold2.Rep4: alpha=0.39224, lambda=4.100786 
## - Fold2.Rep4: alpha=0.39224, lambda=4.100786 
## + Fold2.Rep4: alpha=0.21126, lambda=3.394816 
## - Fold2.Rep4: alpha=0.21126, lambda=3.394816 
## + Fold2.Rep4: alpha=0.20867, lambda=1.714738 
## - Fold2.Rep4: alpha=0.20867, lambda=1.714738 
## + Fold2.Rep4: alpha=0.29287, lambda=0.465785 
## - Fold2.Rep4: alpha=0.29287, lambda=0.465785 
## + Fold2.Rep4: alpha=0.81856, lambda=0.021962 
## - Fold2.Rep4: alpha=0.81856, lambda=0.021962 
## + Fold2.Rep4: alpha=0.66803, lambda=6.064987 
## - Fold2.Rep4: alpha=0.66803, lambda=6.064987 
## + Fold2.Rep4: alpha=0.48714, lambda=0.971740 
## - Fold2.Rep4: alpha=0.48714, lambda=0.971740 
## + Fold2.Rep4: alpha=0.53708, lambda=0.217687 
## - Fold2.Rep4: alpha=0.53708, lambda=0.217687 
## + Fold3.Rep4: alpha=0.88673, lambda=0.188648 
## - Fold3.Rep4: alpha=0.88673, lambda=0.188648 
## + Fold3.Rep4: alpha=0.17251, lambda=0.149375 
## - Fold3.Rep4: alpha=0.17251, lambda=0.149375 
## + Fold3.Rep4: alpha=0.52333, lambda=0.072676 
## - Fold3.Rep4: alpha=0.52333, lambda=0.072676 
## + Fold3.Rep4: alpha=0.89036, lambda=3.971283 
## - Fold3.Rep4: alpha=0.89036, lambda=3.971283 
## + Fold3.Rep4: alpha=0.06876, lambda=0.113433 
## - Fold3.Rep4: alpha=0.06876, lambda=0.113433 
## + Fold3.Rep4: alpha=0.69652, lambda=0.001657 
## - Fold3.Rep4: alpha=0.69652, lambda=0.001657 
## + Fold3.Rep4: alpha=0.82268, lambda=1.898387 
## - Fold3.Rep4: alpha=0.82268, lambda=1.898387 
## + Fold3.Rep4: alpha=0.35681, lambda=0.001551 
## - Fold3.Rep4: alpha=0.35681, lambda=0.001551 
## + Fold3.Rep4: alpha=0.83235, lambda=2.524038 
## - Fold3.Rep4: alpha=0.83235, lambda=2.524038 
## + Fold3.Rep4: alpha=0.88216, lambda=0.001899 
## - Fold3.Rep4: alpha=0.88216, lambda=0.001899 
## + Fold3.Rep4: alpha=0.55337, lambda=2.737403 
## - Fold3.Rep4: alpha=0.55337, lambda=2.737403 
## + Fold3.Rep4: alpha=0.82978, lambda=0.154434 
## - Fold3.Rep4: alpha=0.82978, lambda=0.154434 
## + Fold3.Rep4: alpha=0.31549, lambda=7.029301 
## - Fold3.Rep4: alpha=0.31549, lambda=7.029301 
## + Fold3.Rep4: alpha=0.89748, lambda=0.020774 
## - Fold3.Rep4: alpha=0.89748, lambda=0.020774 
## + Fold3.Rep4: alpha=0.58332, lambda=0.008189 
## - Fold3.Rep4: alpha=0.58332, lambda=0.008189 
## + Fold3.Rep4: alpha=0.66370, lambda=0.005494 
## - Fold3.Rep4: alpha=0.66370, lambda=0.005494 
## + Fold3.Rep4: alpha=0.87945, lambda=0.008348 
## - Fold3.Rep4: alpha=0.87945, lambda=0.008348 
## + Fold3.Rep4: alpha=0.39224, lambda=4.100786 
## - Fold3.Rep4: alpha=0.39224, lambda=4.100786 
## + Fold3.Rep4: alpha=0.21126, lambda=3.394816 
## - Fold3.Rep4: alpha=0.21126, lambda=3.394816 
## + Fold3.Rep4: alpha=0.20867, lambda=1.714738 
## - Fold3.Rep4: alpha=0.20867, lambda=1.714738 
## + Fold3.Rep4: alpha=0.29287, lambda=0.465785 
## - Fold3.Rep4: alpha=0.29287, lambda=0.465785 
## + Fold3.Rep4: alpha=0.81856, lambda=0.021962 
## - Fold3.Rep4: alpha=0.81856, lambda=0.021962 
## + Fold3.Rep4: alpha=0.66803, lambda=6.064987 
## - Fold3.Rep4: alpha=0.66803, lambda=6.064987 
## + Fold3.Rep4: alpha=0.48714, lambda=0.971740 
## - Fold3.Rep4: alpha=0.48714, lambda=0.971740 
## + Fold3.Rep4: alpha=0.53708, lambda=0.217687 
## - Fold3.Rep4: alpha=0.53708, lambda=0.217687 
## + Fold4.Rep4: alpha=0.88673, lambda=0.188648 
## - Fold4.Rep4: alpha=0.88673, lambda=0.188648 
## + Fold4.Rep4: alpha=0.17251, lambda=0.149375 
## - Fold4.Rep4: alpha=0.17251, lambda=0.149375 
## + Fold4.Rep4: alpha=0.52333, lambda=0.072676 
## - Fold4.Rep4: alpha=0.52333, lambda=0.072676 
## + Fold4.Rep4: alpha=0.89036, lambda=3.971283 
## - Fold4.Rep4: alpha=0.89036, lambda=3.971283 
## + Fold4.Rep4: alpha=0.06876, lambda=0.113433 
## - Fold4.Rep4: alpha=0.06876, lambda=0.113433 
## + Fold4.Rep4: alpha=0.69652, lambda=0.001657 
## - Fold4.Rep4: alpha=0.69652, lambda=0.001657 
## + Fold4.Rep4: alpha=0.82268, lambda=1.898387 
## - Fold4.Rep4: alpha=0.82268, lambda=1.898387 
## + Fold4.Rep4: alpha=0.35681, lambda=0.001551 
## - Fold4.Rep4: alpha=0.35681, lambda=0.001551 
## + Fold4.Rep4: alpha=0.83235, lambda=2.524038 
## - Fold4.Rep4: alpha=0.83235, lambda=2.524038 
## + Fold4.Rep4: alpha=0.88216, lambda=0.001899 
## - Fold4.Rep4: alpha=0.88216, lambda=0.001899 
## + Fold4.Rep4: alpha=0.55337, lambda=2.737403 
## - Fold4.Rep4: alpha=0.55337, lambda=2.737403 
## + Fold4.Rep4: alpha=0.82978, lambda=0.154434 
## - Fold4.Rep4: alpha=0.82978, lambda=0.154434 
## + Fold4.Rep4: alpha=0.31549, lambda=7.029301 
## - Fold4.Rep4: alpha=0.31549, lambda=7.029301 
## + Fold4.Rep4: alpha=0.89748, lambda=0.020774 
## - Fold4.Rep4: alpha=0.89748, lambda=0.020774 
## + Fold4.Rep4: alpha=0.58332, lambda=0.008189 
## - Fold4.Rep4: alpha=0.58332, lambda=0.008189 
## + Fold4.Rep4: alpha=0.66370, lambda=0.005494 
## - Fold4.Rep4: alpha=0.66370, lambda=0.005494 
## + Fold4.Rep4: alpha=0.87945, lambda=0.008348 
## - Fold4.Rep4: alpha=0.87945, lambda=0.008348 
## + Fold4.Rep4: alpha=0.39224, lambda=4.100786 
## - Fold4.Rep4: alpha=0.39224, lambda=4.100786 
## + Fold4.Rep4: alpha=0.21126, lambda=3.394816 
## - Fold4.Rep4: alpha=0.21126, lambda=3.394816 
## + Fold4.Rep4: alpha=0.20867, lambda=1.714738 
## - Fold4.Rep4: alpha=0.20867, lambda=1.714738 
## + Fold4.Rep4: alpha=0.29287, lambda=0.465785 
## - Fold4.Rep4: alpha=0.29287, lambda=0.465785 
## + Fold4.Rep4: alpha=0.81856, lambda=0.021962 
## - Fold4.Rep4: alpha=0.81856, lambda=0.021962 
## + Fold4.Rep4: alpha=0.66803, lambda=6.064987 
## - Fold4.Rep4: alpha=0.66803, lambda=6.064987 
## + Fold4.Rep4: alpha=0.48714, lambda=0.971740 
## - Fold4.Rep4: alpha=0.48714, lambda=0.971740 
## + Fold4.Rep4: alpha=0.53708, lambda=0.217687 
## - Fold4.Rep4: alpha=0.53708, lambda=0.217687 
## + Fold5.Rep4: alpha=0.88673, lambda=0.188648 
## - Fold5.Rep4: alpha=0.88673, lambda=0.188648 
## + Fold5.Rep4: alpha=0.17251, lambda=0.149375 
## - Fold5.Rep4: alpha=0.17251, lambda=0.149375 
## + Fold5.Rep4: alpha=0.52333, lambda=0.072676 
## - Fold5.Rep4: alpha=0.52333, lambda=0.072676 
## + Fold5.Rep4: alpha=0.89036, lambda=3.971283 
## - Fold5.Rep4: alpha=0.89036, lambda=3.971283 
## + Fold5.Rep4: alpha=0.06876, lambda=0.113433 
## - Fold5.Rep4: alpha=0.06876, lambda=0.113433 
## + Fold5.Rep4: alpha=0.69652, lambda=0.001657 
## - Fold5.Rep4: alpha=0.69652, lambda=0.001657 
## + Fold5.Rep4: alpha=0.82268, lambda=1.898387 
## - Fold5.Rep4: alpha=0.82268, lambda=1.898387 
## + Fold5.Rep4: alpha=0.35681, lambda=0.001551 
## - Fold5.Rep4: alpha=0.35681, lambda=0.001551 
## + Fold5.Rep4: alpha=0.83235, lambda=2.524038 
## - Fold5.Rep4: alpha=0.83235, lambda=2.524038 
## + Fold5.Rep4: alpha=0.88216, lambda=0.001899 
## - Fold5.Rep4: alpha=0.88216, lambda=0.001899 
## + Fold5.Rep4: alpha=0.55337, lambda=2.737403 
## - Fold5.Rep4: alpha=0.55337, lambda=2.737403 
## + Fold5.Rep4: alpha=0.82978, lambda=0.154434 
## - Fold5.Rep4: alpha=0.82978, lambda=0.154434 
## + Fold5.Rep4: alpha=0.31549, lambda=7.029301 
## - Fold5.Rep4: alpha=0.31549, lambda=7.029301 
## + Fold5.Rep4: alpha=0.89748, lambda=0.020774 
## - Fold5.Rep4: alpha=0.89748, lambda=0.020774 
## + Fold5.Rep4: alpha=0.58332, lambda=0.008189 
## - Fold5.Rep4: alpha=0.58332, lambda=0.008189 
## + Fold5.Rep4: alpha=0.66370, lambda=0.005494 
## - Fold5.Rep4: alpha=0.66370, lambda=0.005494 
## + Fold5.Rep4: alpha=0.87945, lambda=0.008348 
## - Fold5.Rep4: alpha=0.87945, lambda=0.008348 
## + Fold5.Rep4: alpha=0.39224, lambda=4.100786 
## - Fold5.Rep4: alpha=0.39224, lambda=4.100786 
## + Fold5.Rep4: alpha=0.21126, lambda=3.394816 
## - Fold5.Rep4: alpha=0.21126, lambda=3.394816 
## + Fold5.Rep4: alpha=0.20867, lambda=1.714738 
## - Fold5.Rep4: alpha=0.20867, lambda=1.714738 
## + Fold5.Rep4: alpha=0.29287, lambda=0.465785 
## - Fold5.Rep4: alpha=0.29287, lambda=0.465785 
## + Fold5.Rep4: alpha=0.81856, lambda=0.021962 
## - Fold5.Rep4: alpha=0.81856, lambda=0.021962 
## + Fold5.Rep4: alpha=0.66803, lambda=6.064987 
## - Fold5.Rep4: alpha=0.66803, lambda=6.064987 
## + Fold5.Rep4: alpha=0.48714, lambda=0.971740 
## - Fold5.Rep4: alpha=0.48714, lambda=0.971740 
## + Fold5.Rep4: alpha=0.53708, lambda=0.217687 
## - Fold5.Rep4: alpha=0.53708, lambda=0.217687 
## + Fold1.Rep5: alpha=0.88673, lambda=0.188648 
## - Fold1.Rep5: alpha=0.88673, lambda=0.188648 
## + Fold1.Rep5: alpha=0.17251, lambda=0.149375 
## - Fold1.Rep5: alpha=0.17251, lambda=0.149375 
## + Fold1.Rep5: alpha=0.52333, lambda=0.072676 
## - Fold1.Rep5: alpha=0.52333, lambda=0.072676 
## + Fold1.Rep5: alpha=0.89036, lambda=3.971283 
## - Fold1.Rep5: alpha=0.89036, lambda=3.971283 
## + Fold1.Rep5: alpha=0.06876, lambda=0.113433 
## - Fold1.Rep5: alpha=0.06876, lambda=0.113433 
## + Fold1.Rep5: alpha=0.69652, lambda=0.001657 
## - Fold1.Rep5: alpha=0.69652, lambda=0.001657 
## + Fold1.Rep5: alpha=0.82268, lambda=1.898387 
## - Fold1.Rep5: alpha=0.82268, lambda=1.898387 
## + Fold1.Rep5: alpha=0.35681, lambda=0.001551 
## - Fold1.Rep5: alpha=0.35681, lambda=0.001551 
## + Fold1.Rep5: alpha=0.83235, lambda=2.524038 
## - Fold1.Rep5: alpha=0.83235, lambda=2.524038 
## + Fold1.Rep5: alpha=0.88216, lambda=0.001899 
## - Fold1.Rep5: alpha=0.88216, lambda=0.001899 
## + Fold1.Rep5: alpha=0.55337, lambda=2.737403 
## - Fold1.Rep5: alpha=0.55337, lambda=2.737403 
## + Fold1.Rep5: alpha=0.82978, lambda=0.154434 
## - Fold1.Rep5: alpha=0.82978, lambda=0.154434 
## + Fold1.Rep5: alpha=0.31549, lambda=7.029301 
## - Fold1.Rep5: alpha=0.31549, lambda=7.029301 
## + Fold1.Rep5: alpha=0.89748, lambda=0.020774 
## - Fold1.Rep5: alpha=0.89748, lambda=0.020774 
## + Fold1.Rep5: alpha=0.58332, lambda=0.008189 
## - Fold1.Rep5: alpha=0.58332, lambda=0.008189 
## + Fold1.Rep5: alpha=0.66370, lambda=0.005494 
## - Fold1.Rep5: alpha=0.66370, lambda=0.005494 
## + Fold1.Rep5: alpha=0.87945, lambda=0.008348 
## - Fold1.Rep5: alpha=0.87945, lambda=0.008348 
## + Fold1.Rep5: alpha=0.39224, lambda=4.100786 
## - Fold1.Rep5: alpha=0.39224, lambda=4.100786 
## + Fold1.Rep5: alpha=0.21126, lambda=3.394816 
## - Fold1.Rep5: alpha=0.21126, lambda=3.394816 
## + Fold1.Rep5: alpha=0.20867, lambda=1.714738 
## - Fold1.Rep5: alpha=0.20867, lambda=1.714738 
## + Fold1.Rep5: alpha=0.29287, lambda=0.465785 
## - Fold1.Rep5: alpha=0.29287, lambda=0.465785 
## + Fold1.Rep5: alpha=0.81856, lambda=0.021962 
## - Fold1.Rep5: alpha=0.81856, lambda=0.021962 
## + Fold1.Rep5: alpha=0.66803, lambda=6.064987 
## - Fold1.Rep5: alpha=0.66803, lambda=6.064987 
## + Fold1.Rep5: alpha=0.48714, lambda=0.971740 
## - Fold1.Rep5: alpha=0.48714, lambda=0.971740 
## + Fold1.Rep5: alpha=0.53708, lambda=0.217687 
## - Fold1.Rep5: alpha=0.53708, lambda=0.217687 
## + Fold2.Rep5: alpha=0.88673, lambda=0.188648 
## - Fold2.Rep5: alpha=0.88673, lambda=0.188648 
## + Fold2.Rep5: alpha=0.17251, lambda=0.149375 
## - Fold2.Rep5: alpha=0.17251, lambda=0.149375 
## + Fold2.Rep5: alpha=0.52333, lambda=0.072676 
## - Fold2.Rep5: alpha=0.52333, lambda=0.072676 
## + Fold2.Rep5: alpha=0.89036, lambda=3.971283 
## - Fold2.Rep5: alpha=0.89036, lambda=3.971283 
## + Fold2.Rep5: alpha=0.06876, lambda=0.113433 
## - Fold2.Rep5: alpha=0.06876, lambda=0.113433 
## + Fold2.Rep5: alpha=0.69652, lambda=0.001657 
## - Fold2.Rep5: alpha=0.69652, lambda=0.001657 
## + Fold2.Rep5: alpha=0.82268, lambda=1.898387 
## - Fold2.Rep5: alpha=0.82268, lambda=1.898387 
## + Fold2.Rep5: alpha=0.35681, lambda=0.001551 
## - Fold2.Rep5: alpha=0.35681, lambda=0.001551 
## + Fold2.Rep5: alpha=0.83235, lambda=2.524038 
## - Fold2.Rep5: alpha=0.83235, lambda=2.524038 
## + Fold2.Rep5: alpha=0.88216, lambda=0.001899 
## - Fold2.Rep5: alpha=0.88216, lambda=0.001899 
## + Fold2.Rep5: alpha=0.55337, lambda=2.737403 
## - Fold2.Rep5: alpha=0.55337, lambda=2.737403 
## + Fold2.Rep5: alpha=0.82978, lambda=0.154434 
## - Fold2.Rep5: alpha=0.82978, lambda=0.154434 
## + Fold2.Rep5: alpha=0.31549, lambda=7.029301 
## - Fold2.Rep5: alpha=0.31549, lambda=7.029301 
## + Fold2.Rep5: alpha=0.89748, lambda=0.020774 
## - Fold2.Rep5: alpha=0.89748, lambda=0.020774 
## + Fold2.Rep5: alpha=0.58332, lambda=0.008189 
## - Fold2.Rep5: alpha=0.58332, lambda=0.008189 
## + Fold2.Rep5: alpha=0.66370, lambda=0.005494 
## - Fold2.Rep5: alpha=0.66370, lambda=0.005494 
## + Fold2.Rep5: alpha=0.87945, lambda=0.008348 
## - Fold2.Rep5: alpha=0.87945, lambda=0.008348 
## + Fold2.Rep5: alpha=0.39224, lambda=4.100786 
## - Fold2.Rep5: alpha=0.39224, lambda=4.100786 
## + Fold2.Rep5: alpha=0.21126, lambda=3.394816 
## - Fold2.Rep5: alpha=0.21126, lambda=3.394816 
## + Fold2.Rep5: alpha=0.20867, lambda=1.714738 
## - Fold2.Rep5: alpha=0.20867, lambda=1.714738 
## + Fold2.Rep5: alpha=0.29287, lambda=0.465785 
## - Fold2.Rep5: alpha=0.29287, lambda=0.465785 
## + Fold2.Rep5: alpha=0.81856, lambda=0.021962 
## - Fold2.Rep5: alpha=0.81856, lambda=0.021962 
## + Fold2.Rep5: alpha=0.66803, lambda=6.064987 
## - Fold2.Rep5: alpha=0.66803, lambda=6.064987 
## + Fold2.Rep5: alpha=0.48714, lambda=0.971740 
## - Fold2.Rep5: alpha=0.48714, lambda=0.971740 
## + Fold2.Rep5: alpha=0.53708, lambda=0.217687 
## - Fold2.Rep5: alpha=0.53708, lambda=0.217687 
## + Fold3.Rep5: alpha=0.88673, lambda=0.188648 
## - Fold3.Rep5: alpha=0.88673, lambda=0.188648 
## + Fold3.Rep5: alpha=0.17251, lambda=0.149375 
## - Fold3.Rep5: alpha=0.17251, lambda=0.149375 
## + Fold3.Rep5: alpha=0.52333, lambda=0.072676 
## - Fold3.Rep5: alpha=0.52333, lambda=0.072676 
## + Fold3.Rep5: alpha=0.89036, lambda=3.971283 
## - Fold3.Rep5: alpha=0.89036, lambda=3.971283 
## + Fold3.Rep5: alpha=0.06876, lambda=0.113433 
## - Fold3.Rep5: alpha=0.06876, lambda=0.113433 
## + Fold3.Rep5: alpha=0.69652, lambda=0.001657 
## - Fold3.Rep5: alpha=0.69652, lambda=0.001657 
## + Fold3.Rep5: alpha=0.82268, lambda=1.898387 
## - Fold3.Rep5: alpha=0.82268, lambda=1.898387 
## + Fold3.Rep5: alpha=0.35681, lambda=0.001551 
## - Fold3.Rep5: alpha=0.35681, lambda=0.001551 
## + Fold3.Rep5: alpha=0.83235, lambda=2.524038 
## - Fold3.Rep5: alpha=0.83235, lambda=2.524038 
## + Fold3.Rep5: alpha=0.88216, lambda=0.001899 
## - Fold3.Rep5: alpha=0.88216, lambda=0.001899 
## + Fold3.Rep5: alpha=0.55337, lambda=2.737403 
## - Fold3.Rep5: alpha=0.55337, lambda=2.737403 
## + Fold3.Rep5: alpha=0.82978, lambda=0.154434 
## - Fold3.Rep5: alpha=0.82978, lambda=0.154434 
## + Fold3.Rep5: alpha=0.31549, lambda=7.029301 
## - Fold3.Rep5: alpha=0.31549, lambda=7.029301 
## + Fold3.Rep5: alpha=0.89748, lambda=0.020774 
## - Fold3.Rep5: alpha=0.89748, lambda=0.020774 
## + Fold3.Rep5: alpha=0.58332, lambda=0.008189 
## - Fold3.Rep5: alpha=0.58332, lambda=0.008189 
## + Fold3.Rep5: alpha=0.66370, lambda=0.005494 
## - Fold3.Rep5: alpha=0.66370, lambda=0.005494 
## + Fold3.Rep5: alpha=0.87945, lambda=0.008348 
## - Fold3.Rep5: alpha=0.87945, lambda=0.008348 
## + Fold3.Rep5: alpha=0.39224, lambda=4.100786 
## - Fold3.Rep5: alpha=0.39224, lambda=4.100786 
## + Fold3.Rep5: alpha=0.21126, lambda=3.394816 
## - Fold3.Rep5: alpha=0.21126, lambda=3.394816 
## + Fold3.Rep5: alpha=0.20867, lambda=1.714738 
## - Fold3.Rep5: alpha=0.20867, lambda=1.714738 
## + Fold3.Rep5: alpha=0.29287, lambda=0.465785 
## - Fold3.Rep5: alpha=0.29287, lambda=0.465785 
## + Fold3.Rep5: alpha=0.81856, lambda=0.021962 
## - Fold3.Rep5: alpha=0.81856, lambda=0.021962 
## + Fold3.Rep5: alpha=0.66803, lambda=6.064987 
## - Fold3.Rep5: alpha=0.66803, lambda=6.064987 
## + Fold3.Rep5: alpha=0.48714, lambda=0.971740 
## - Fold3.Rep5: alpha=0.48714, lambda=0.971740 
## + Fold3.Rep5: alpha=0.53708, lambda=0.217687 
## - Fold3.Rep5: alpha=0.53708, lambda=0.217687 
## + Fold4.Rep5: alpha=0.88673, lambda=0.188648 
## - Fold4.Rep5: alpha=0.88673, lambda=0.188648 
## + Fold4.Rep5: alpha=0.17251, lambda=0.149375 
## - Fold4.Rep5: alpha=0.17251, lambda=0.149375 
## + Fold4.Rep5: alpha=0.52333, lambda=0.072676 
## - Fold4.Rep5: alpha=0.52333, lambda=0.072676 
## + Fold4.Rep5: alpha=0.89036, lambda=3.971283 
## - Fold4.Rep5: alpha=0.89036, lambda=3.971283 
## + Fold4.Rep5: alpha=0.06876, lambda=0.113433 
## - Fold4.Rep5: alpha=0.06876, lambda=0.113433 
## + Fold4.Rep5: alpha=0.69652, lambda=0.001657 
## - Fold4.Rep5: alpha=0.69652, lambda=0.001657 
## + Fold4.Rep5: alpha=0.82268, lambda=1.898387 
## - Fold4.Rep5: alpha=0.82268, lambda=1.898387 
## + Fold4.Rep5: alpha=0.35681, lambda=0.001551 
## - Fold4.Rep5: alpha=0.35681, lambda=0.001551 
## + Fold4.Rep5: alpha=0.83235, lambda=2.524038 
## - Fold4.Rep5: alpha=0.83235, lambda=2.524038 
## + Fold4.Rep5: alpha=0.88216, lambda=0.001899 
## - Fold4.Rep5: alpha=0.88216, lambda=0.001899 
## + Fold4.Rep5: alpha=0.55337, lambda=2.737403 
## - Fold4.Rep5: alpha=0.55337, lambda=2.737403 
## + Fold4.Rep5: alpha=0.82978, lambda=0.154434 
## - Fold4.Rep5: alpha=0.82978, lambda=0.154434 
## + Fold4.Rep5: alpha=0.31549, lambda=7.029301 
## - Fold4.Rep5: alpha=0.31549, lambda=7.029301 
## + Fold4.Rep5: alpha=0.89748, lambda=0.020774 
## - Fold4.Rep5: alpha=0.89748, lambda=0.020774 
## + Fold4.Rep5: alpha=0.58332, lambda=0.008189 
## - Fold4.Rep5: alpha=0.58332, lambda=0.008189 
## + Fold4.Rep5: alpha=0.66370, lambda=0.005494 
## - Fold4.Rep5: alpha=0.66370, lambda=0.005494 
## + Fold4.Rep5: alpha=0.87945, lambda=0.008348 
## - Fold4.Rep5: alpha=0.87945, lambda=0.008348 
## + Fold4.Rep5: alpha=0.39224, lambda=4.100786 
## - Fold4.Rep5: alpha=0.39224, lambda=4.100786 
## + Fold4.Rep5: alpha=0.21126, lambda=3.394816 
## - Fold4.Rep5: alpha=0.21126, lambda=3.394816 
## + Fold4.Rep5: alpha=0.20867, lambda=1.714738 
## - Fold4.Rep5: alpha=0.20867, lambda=1.714738 
## + Fold4.Rep5: alpha=0.29287, lambda=0.465785 
## - Fold4.Rep5: alpha=0.29287, lambda=0.465785 
## + Fold4.Rep5: alpha=0.81856, lambda=0.021962 
## - Fold4.Rep5: alpha=0.81856, lambda=0.021962 
## + Fold4.Rep5: alpha=0.66803, lambda=6.064987 
## - Fold4.Rep5: alpha=0.66803, lambda=6.064987 
## + Fold4.Rep5: alpha=0.48714, lambda=0.971740 
## - Fold4.Rep5: alpha=0.48714, lambda=0.971740 
## + Fold4.Rep5: alpha=0.53708, lambda=0.217687 
## - Fold4.Rep5: alpha=0.53708, lambda=0.217687 
## + Fold5.Rep5: alpha=0.88673, lambda=0.188648 
## - Fold5.Rep5: alpha=0.88673, lambda=0.188648 
## + Fold5.Rep5: alpha=0.17251, lambda=0.149375 
## - Fold5.Rep5: alpha=0.17251, lambda=0.149375 
## + Fold5.Rep5: alpha=0.52333, lambda=0.072676 
## - Fold5.Rep5: alpha=0.52333, lambda=0.072676 
## + Fold5.Rep5: alpha=0.89036, lambda=3.971283 
## - Fold5.Rep5: alpha=0.89036, lambda=3.971283 
## + Fold5.Rep5: alpha=0.06876, lambda=0.113433 
## - Fold5.Rep5: alpha=0.06876, lambda=0.113433 
## + Fold5.Rep5: alpha=0.69652, lambda=0.001657 
## - Fold5.Rep5: alpha=0.69652, lambda=0.001657 
## + Fold5.Rep5: alpha=0.82268, lambda=1.898387 
## - Fold5.Rep5: alpha=0.82268, lambda=1.898387 
## + Fold5.Rep5: alpha=0.35681, lambda=0.001551 
## - Fold5.Rep5: alpha=0.35681, lambda=0.001551 
## + Fold5.Rep5: alpha=0.83235, lambda=2.524038 
## - Fold5.Rep5: alpha=0.83235, lambda=2.524038 
## + Fold5.Rep5: alpha=0.88216, lambda=0.001899 
## - Fold5.Rep5: alpha=0.88216, lambda=0.001899 
## + Fold5.Rep5: alpha=0.55337, lambda=2.737403 
## - Fold5.Rep5: alpha=0.55337, lambda=2.737403 
## + Fold5.Rep5: alpha=0.82978, lambda=0.154434 
## - Fold5.Rep5: alpha=0.82978, lambda=0.154434 
## + Fold5.Rep5: alpha=0.31549, lambda=7.029301 
## - Fold5.Rep5: alpha=0.31549, lambda=7.029301 
## + Fold5.Rep5: alpha=0.89748, lambda=0.020774 
## - Fold5.Rep5: alpha=0.89748, lambda=0.020774 
## + Fold5.Rep5: alpha=0.58332, lambda=0.008189 
## - Fold5.Rep5: alpha=0.58332, lambda=0.008189 
## + Fold5.Rep5: alpha=0.66370, lambda=0.005494 
## - Fold5.Rep5: alpha=0.66370, lambda=0.005494 
## + Fold5.Rep5: alpha=0.87945, lambda=0.008348 
## - Fold5.Rep5: alpha=0.87945, lambda=0.008348 
## + Fold5.Rep5: alpha=0.39224, lambda=4.100786 
## - Fold5.Rep5: alpha=0.39224, lambda=4.100786 
## + Fold5.Rep5: alpha=0.21126, lambda=3.394816 
## - Fold5.Rep5: alpha=0.21126, lambda=3.394816 
## + Fold5.Rep5: alpha=0.20867, lambda=1.714738 
## - Fold5.Rep5: alpha=0.20867, lambda=1.714738 
## + Fold5.Rep5: alpha=0.29287, lambda=0.465785 
## - Fold5.Rep5: alpha=0.29287, lambda=0.465785 
## + Fold5.Rep5: alpha=0.81856, lambda=0.021962 
## - Fold5.Rep5: alpha=0.81856, lambda=0.021962 
## + Fold5.Rep5: alpha=0.66803, lambda=6.064987 
## - Fold5.Rep5: alpha=0.66803, lambda=6.064987 
## + Fold5.Rep5: alpha=0.48714, lambda=0.971740 
## - Fold5.Rep5: alpha=0.48714, lambda=0.971740 
## + Fold5.Rep5: alpha=0.53708, lambda=0.217687 
## - Fold5.Rep5: alpha=0.53708, lambda=0.217687 
## Aggregating results
## Selecting tuning parameters
## Fitting alpha = 0.583, lambda = 0.00819 on full training set
elastic_model 
## glmnet 
## 
## 84525 samples
##    14 predictor
## 
## Pre-processing: centered (14), scaled (14) 
## Resampling: Cross-Validated (5 fold, repeated 5 times) 
## Summary of sample sizes: 67621, 67619, 67620, 67620, 67620, 67621, ... 
## Resampling results across tuning parameters:
## 
##   alpha       lambda       RMSE       Rsquared   MAE     
##   0.06876433  0.113432800   8.735923  0.6847304  6.361206
##   0.17250896  0.149374972   8.736850  0.6846874  6.361618
##   0.20867316  1.714738322   8.847165  0.6815835  6.557331
##   0.21125721  3.394815536   9.045809  0.6783818  6.825648
##   0.29286574  0.465784791   8.752501  0.6840097  6.388511
##   0.31549376  7.029300792   9.743641  0.6771812  7.601590
##   0.35680771  0.001551316   8.735681  0.6847318  6.354317
##   0.39223995  4.100785818   9.233766  0.6800352  7.063697
##   0.48713970  0.971739738   8.805351  0.6822081  6.469126
##   0.52333486  0.072676349   8.736796  0.6846624  6.353545
##   0.53708309  0.217686804   8.744468  0.6842437  6.362709
##   0.55336682  2.737403145   9.045971  0.6818364  6.839039
##   0.58332201  0.008188642   8.735672  0.6847297  6.352686
##   0.66370131  0.005493856   8.735676  0.6847288  6.352366
##   0.66803380  6.064987237  10.094770  0.6819633  7.986012
##   0.69651918  0.001657071   8.735681  0.6847283  6.352238
##   0.81856105  0.021962223   8.735706  0.6847262  6.351891
##   0.82267651  1.898387317   8.957145  0.6819579  6.707539
##   0.82977965  0.154433921   8.744647  0.6841816  6.356173
##   0.83235296  2.524038284   9.098348  0.6816817  6.900946
##   0.87944868  0.008348323   8.735705  0.6847261  6.351754
##   0.88215644  0.001898939   8.735704  0.6847261  6.351749
##   0.88673137  0.188647932   8.749121  0.6839133  6.359207
##   0.89035794  3.971283445   9.608186  0.6788287  7.495460
##   0.89747707  0.020774229   8.735702  0.6847262  6.351708
## 
## RMSE was used to select the optimal model using the smallest value.
## The final values used for the model were alpha = 0.583322 and lambda
##  = 0.008188642.
# RMSE was used to select the optimal model using the smallest value.

# plot
plot(elastic_model, main = "Elastic Net Regression")

# print out values from best tuned model
best_elastic <- elastic_model$results %>%
  filter(alpha == elastic_model$bestTune$alpha, lambda == elastic_model$bestTune$lambda)
best_elastic
##      alpha      lambda     RMSE  Rsquared      MAE     RMSESD  RsquaredSD
## 1 0.583322 0.008188642 8.735672 0.6847297 6.352686 0.05325549 0.003896935
##        MAESD
## 1 0.02982672

Insert inrepretation of this result. The elastic net algorithm does tune and cross validate on its own, so there is no need for us to perform further cross validation or tuning.

Now that we have our model, we want to make a prediction on our test data. To do this, we use the predict() function to get the test mean square error. Later we will compare the test MSEs of different functions to decide which model is optimal for our data.

# elastic model prediction on test data (to have prediction code)
elastic.pred <- predict(elastic_model, x.eltest)

# evaluate mse on the test data
elastic_mse <- mean((elastic.pred - y.eltest)^2)
elastic_mse
## [1] 76.22993

Bayesian Additive Regression Trees (BART)

The BART method uses decision trees for regression, constructing each tree randomly, similar to bagging and random forest models. Each new tree is trying to capture “signal” that is not accounted for by the rest of the trees. In the BART model, K is the number of regression trees and B is the number of iterations that the BART will run through.

Below is a description of the algorithm we used to construct our BART model. from ISLR textbook

First, we got our training and testing data and split them into Xtrain, Ytrain, Xtest, and Ytest for the BART model. Then we were able to use the gbart() function to fit a model using BART.

library(BART)
## Loading required package: nlme
## 
## Attaching package: 'nlme'
## The following object is masked from 'package:dplyr':
## 
##     collapse
## Loading required package: nnet
## Loading required package: survival
## 
## Attaching package: 'survival'
## The following object is masked from 'package:caret':
## 
##     cluster
# BART Implementation
Ytrainbart <- train$popularity %>% scale(center = TRUE, scale = TRUE) # from lab 5
Xtrainbart <- train %>% select(-popularity) %>% scale(center = TRUE, scale = TRUE)

Ytestbart <- test$popularity %>% scale(center = TRUE, scale = TRUE)
Xtestbart <- test %>% select(-popularity) %>% scale(center = TRUE, scale = TRUE)

# set.seed (1)
# bartfit <- gbart(Xtrainbart, Ytrainbart, x.test = Xtestbart)

Next, we found the test error for BART model:

# Yhat.bart <- bartfit$yhat.test.mean
# mean((Ytest - Yhat.bart)^2) # test error

Next, we found that each variable appeared [insert here] times in the collection of trees:

# How many times each variable appeared in the collection of trees
# ord <- order(bartfit$varcount.mean , decreasing = T)
# bartfit$varcount.mean[ord]

Finally, we implemented k-fold cross validation with our BART model:

# do chunk k-fold cv with BART
do.chunk.bart <- function(chunkid, folddef, Xdat, Ydat, ...){
  # Get training index
  train = (folddef!=chunkid)
  # Get training set by the above index
  Xtr = Xdat[train,]
  # Get responses in training set
  Ytr = Ydat[train]
  # Get validation set
  Xval = Xdat[!train,]
  # Get responses in validation set
  Yval = Ydat[!train]
  # Predict training labels
  predYtr = gbart(Xtr, Ytr, x.test = Xtr)
  # Predict validation labels
  predYval = gbart(Xtr , Ytr , x.test = Xval)
  data.frame(fold = chunkid,
    train.error = mean((Ytrainbart - predYtr$yhat.train.mean)^2), # Training error for each fold
    val.error = mean((Ytestbart - predYval$yhat.test.mean)^2))  # Validation error for each fold
}
# k-fold CV on BART
nfold = 5
# cut: divides all training observations into 3 intervals;
# labels = FALSE instructs R to use integers to code different intervals
set.seed(3)
folds = cut(1:nrow(train), breaks=nfold, labels=FALSE) %>% sample()
folds
##     [1] 4 3 3 5 4 1 4 4 2 5 5 4 3 2 5 4 5 4 5 2 1 1 2 3 1 4 5 3 4 4 4 5 1 3 2 2
##    [37] 1 1 3 1 2 2 5 3 1 3 4 5 5 1 2 1 5 4 1 1 4 3 2 5 1 2 4 3 2 2 3 1 2 1 5 3
##    [73] 3 5 2 3 2 1 5 3 4 3 3 5 5 2 5 2 1 2 3 3 4 3 3 3 4 5 4 4 5 2 3 4 4 5 5 5
##   [109] 5 2 1 4 5 4 2 4 1 4 1 2 5 4 2 5 2 3 2 2 4 1 4 4 3 2 5 3 4 3 3 3 2 3 1 1
##   [145] 2 3 4 3 3 1 2 2 4 2 4 2 3 4 1 1 3 4 4 1 5 2 3 1 3 1 1 4 3 1 2 5 2 3 5 5
##   [181] 4 4 1 2 3 3 2 2 2 2 3 4 4 5 1 4 4 3 4 1 5 5 2 3 4 1 5 5 3 2 1 5 1 5 2 1
##   [217] 4 4 3 2 1 3 3 4 4 3 3 3 3 1 2 4 1 5 5 4 1 5 1 2 3 1 5 1 3 1 2 2 5 2 3 3
##   [253] 1 1 2 4 1 2 2 4 3 2 1 1 4 5 1 2 1 5 1 4 4 2 2 2 3 1 5 2 2 2 2 5 5 3 1 3
##   [289] 5 3 3 1 3 4 5 5 3 3 3 4 2 2 4 1 5 4 4 3 5 3 3 4 5 1 4 1 3 1 1 1 4 1 3 1
##   [325] 1 2 1 5 2 1 4 3 1 4 3 3 3 1 5 4 3 2 2 3 1 3 2 5 3 1 4 2 1 2 4 3 2 5 2 3
##   [361] 5 3 3 1 5 1 2 1 1 2 5 2 3 3 5 4 4 1 3 5 2 4 4 4 5 1 3 4 1 2 3 2 4 2 2 4
##   [397] 2 3 4 2 2 3 1 2 1 2 3 3 5 4 4 4 2 1 3 3 2 1 1 4 2 4 4 3 4 5 3 1 2 2 1 2
##   [433] 5 2 5 3 1 4 5 3 3 5 2 2 3 1 1 2 2 5 2 2 2 1 1 5 1 2 2 2 4 5 1 1 3 1 4 2
##   [469] 3 4 2 3 2 1 3 3 4 4 3 1 2 3 5 1 3 1 4 5 2 2 5 2 2 2 1 3 5 2 5 2 3 1 1 3
##   [505] 3 2 1 1 5 2 4 5 4 1 3 5 3 1 5 2 2 1 1 4 2 3 1 4 4 5 5 5 5 3 1 3 2 1 2 3
##   [541] 1 5 2 4 1 4 3 4 4 1 4 2 3 3 4 5 4 1 4 3 4 5 4 3 4 4 2 4 4 2 1 3 3 5 3 5
##   [577] 3 4 5 5 2 2 1 2 5 3 3 3 2 2 5 4 5 3 3 3 2 5 1 5 1 5 1 1 2 2 1 3 1 5 1 3
##   [613] 1 5 1 5 4 4 4 2 2 4 4 5 5 3 4 4 5 2 3 3 5 3 4 3 2 4 2 4 3 4 5 3 2 2 3 4
##   [649] 3 4 5 4 5 1 4 4 1 5 1 4 5 2 4 5 5 2 4 2 1 3 1 5 5 3 5 1 3 2 1 2 2 4 3 1
##   [685] 3 2 3 5 2 3 2 2 1 5 2 1 1 5 3 2 5 5 3 4 5 2 3 1 4 3 3 5 2 5 1 4 3 2 5 2
##   [721] 1 5 5 1 5 1 4 3 4 3 2 2 4 4 4 2 4 5 5 3 5 4 3 5 2 1 3 2 4 3 1 4 2 3 3 3
##   [757] 4 1 3 1 4 3 3 2 4 4 3 5 3 2 4 3 5 2 3 3 3 2 4 3 4 1 4 3 1 2 3 1 1 5 3 4
##   [793] 1 4 1 2 1 4 3 5 2 1 1 5 3 2 2 1 3 1 1 2 1 3 1 5 5 5 4 1 2 4 2 2 1 3 4 5
##   [829] 5 5 1 3 3 4 5 4 3 4 3 4 1 4 4 2 5 2 3 1 5 3 4 2 3 5 3 2 4 2 5 5 5 5 4 3
##   [865] 4 1 3 2 3 1 1 5 1 4 2 2 3 4 2 1 3 4 5 5 2 2 4 5 4 1 2 1 4 1 2 1 5 1 4 1
##   [901] 4 4 5 4 5 4 4 3 4 3 1 4 3 5 3 1 1 4 5 3 3 5 5 4 4 1 5 1 1 3 3 3 1 1 4 1
##   [937] 3 1 4 3 1 4 1 2 1 2 5 5 2 3 2 5 2 3 2 3 3 5 5 3 3 5 5 5 2 5 3 2 2 1 2 4
##   [973] 4 3 2 2 4 5 2 5 5 1 2 2 1 5 2 2 4 3 2 5 2 3 3 4 2 2 3 2 5 4 4 5 3 3 2 4
##  [1009] 2 3 3 4 5 2 5 4 2 2 3 4 4 5 4 5 4 3 2 3 4 1 5 4 1 3 5 3 2 5 5 5 2 4 5 3
##  [1045] 2 4 3 1 3 1 1 5 5 1 3 2 5 5 4 2 1 2 1 2 4 3 4 4 2 3 4 1 4 2 2 2 4 5 3 4
##  [1081] 2 1 5 1 3 1 4 3 3 4 5 5 5 3 3 2 4 3 4 2 1 5 1 5 4 5 5 5 3 1 5 2 1 4 3 2
##  [1117] 4 5 5 2 2 3 1 1 5 3 2 3 5 4 4 4 4 4 2 3 5 1 4 5 5 5 2 3 2 5 4 2 3 4 4 4
##  [1153] 1 3 4 5 5 1 5 3 3 2 5 1 3 4 5 2 1 1 2 2 3 5 5 4 5 2 3 5 3 5 2 3 3 4 4 2
##  [1189] 5 5 1 1 5 2 5 2 5 4 2 2 3 1 2 2 1 2 2 4 3 4 3 2 5 2 4 3 3 5 1 3 1 4 4 5
##  [1225] 4 5 1 2 2 1 3 3 5 3 4 5 1 1 5 5 1 5 4 1 3 1 2 5 4 4 3 5 2 2 3 5 5 4 1 3
##  [1261] 4 2 5 1 1 1 5 5 5 3 3 3 3 3 5 4 4 5 3 5 1 5 4 1 5 5 2 4 5 1 4 4 3 2 2 3
##  [1297] 1 2 5 4 3 2 4 2 3 5 1 4 5 1 5 5 3 1 2 4 5 1 4 5 1 2 3 3 5 5 4 2 2 1 5 1
##  [1333] 4 1 1 5 4 4 3 4 1 1 2 1 2 5 1 3 5 3 5 4 1 4 3 3 4 1 5 2 4 1 5 5 2 2 5 4
##  [1369] 5 3 3 3 1 3 2 4 4 4 1 4 5 5 1 2 5 5 3 4 5 3 1 4 5 4 1 3 1 5 5 1 5 5 3 2
##  [1405] 2 1 2 3 5 4 4 1 4 3 4 3 2 5 3 3 1 1 5 4 1 2 3 5 5 2 1 4 1 4 1 4 2 4 2 1
##  [1441] 4 1 4 5 1 3 1 2 1 1 2 4 2 3 1 1 5 1 3 1 2 4 3 4 4 1 5 2 5 1 1 1 2 4 3 3
##  [1477] 3 5 4 3 4 5 2 5 1 3 1 2 2 2 1 3 1 1 2 2 3 5 1 1 5 2 1 1 5 2 5 5 1 1 1 1
##  [1513] 2 2 5 1 5 4 1 1 1 1 1 3 1 1 1 1 2 2 5 1 4 1 4 2 3 4 2 4 5 1 4 4 3 3 1 2
##  [1549] 2 5 4 1 1 1 1 3 4 4 5 4 1 5 3 5 5 1 3 4 2 2 4 2 5 4 4 4 1 2 5 5 4 2 2 3
##  [1585] 1 3 2 3 4 4 1 1 2 5 1 4 4 3 4 5 2 2 2 1 4 4 2 1 4 1 1 5 2 5 2 2 4 4 4 5
##  [1621] 2 4 5 2 5 2 4 5 2 2 1 3 2 1 3 3 3 3 5 5 2 1 1 2 2 5 1 1 4 5 5 4 2 4 2 3
##  [1657] 3 3 5 2 4 4 1 5 4 2 1 5 2 5 3 4 5 2 4 2 4 5 1 5 2 4 3 4 2 3 5 5 1 2 2 2
##  [1693] 4 1 1 2 1 2 5 2 5 2 1 3 1 1 2 5 2 3 2 2 4 2 3 1 3 1 2 1 5 4 3 4 4 5 2 4
##  [1729] 4 3 4 1 2 3 1 1 5 3 1 2 4 5 3 4 1 3 2 2 4 5 3 3 2 5 2 3 1 2 4 3 2 1 1 3
##  [1765] 2 5 1 1 2 5 1 1 4 1 5 2 5 1 3 4 2 1 4 1 3 2 4 5 4 4 4 2 1 1 3 5 1 3 2 5
##  [1801] 1 1 4 4 1 2 2 4 5 1 5 2 1 1 2 5 5 4 3 3 1 5 2 3 1 1 3 2 5 3 1 2 2 2 1 2
##  [1837] 3 5 2 2 4 5 4 1 4 4 1 1 5 5 3 1 5 4 3 5 1 4 2 3 4 4 1 4 4 5 1 2 5 2 5 3
##  [1873] 4 2 3 2 1 3 2 5 1 1 4 3 5 3 3 5 5 3 1 3 3 5 1 1 4 5 1 4 4 4 3 3 5 3 3 1
##  [1909] 3 1 5 1 1 4 4 3 2 1 4 3 5 1 4 4 1 4 4 4 3 5 5 5 1 1 5 4 2 4 3 4 1 2 3 5
##  [1945] 3 3 4 2 5 1 5 5 4 1 5 1 4 3 4 5 3 4 2 3 5 1 2 5 2 2 1 5 5 5 2 2 4 5 4 4
##  [1981] 3 4 3 4 5 1 3 1 1 1 1 5 3 2 4 3 3 1 1 1 5 3 4 5 4 1 5 1 2 2 1 4 3 3 5 2
##  [2017] 4 5 3 1 4 3 5 1 1 2 5 1 3 5 4 2 2 3 1 4 3 1 2 1 5 4 3 3 1 5 2 1 4 1 3 2
##  [2053] 2 3 4 4 4 2 4 4 2 1 3 3 4 5 1 2 1 1 1 5 1 5 4 3 4 2 2 5 2 3 4 1 4 4 4 4
##  [2089] 1 5 5 1 1 5 5 5 5 2 1 3 1 2 1 3 4 1 3 3 2 3 3 5 4 1 1 4 2 3 4 4 5 4 3 1
##  [2125] 3 4 2 3 3 4 3 4 4 5 2 2 1 1 2 2 3 4 3 2 5 5 3 2 3 5 1 5 2 4 5 2 5 1 3 5
##  [2161] 1 2 1 1 1 2 1 3 1 3 4 2 1 1 2 1 1 1 2 1 4 1 3 5 3 2 4 4 4 3 5 5 4 5 4 2
##  [2197] 1 1 2 3 3 3 2 3 3 5 3 2 1 5 3 4 3 3 1 5 2 5 1 3 4 4 1 4 3 4 3 3 4 2 5 2
##  [2233] 4 4 2 1 1 1 5 4 5 4 3 2 1 3 1 5 3 3 4 2 1 2 4 3 4 3 5 4 1 3 4 2 4 3 2 1
##  [2269] 2 3 5 1 5 3 4 2 4 5 4 2 5 5 5 3 2 3 3 3 3 4 2 3 3 3 3 5 5 2 5 5 3 2 2 3
##  [2305] 2 4 4 3 4 1 2 1 5 4 4 1 4 1 5 3 5 5 1 2 4 1 5 5 4 3 2 5 5 4 1 3 3 5 5 1
##  [2341] 5 5 4 1 1 1 5 3 4 2 1 3 1 2 2 3 2 2 3 3 3 2 1 3 1 2 5 1 1 5 1 3 3 1 5 4
##  [2377] 2 1 1 5 3 2 1 1 2 3 1 5 5 2 3 3 4 1 2 1 5 3 5 1 1 5 5 2 2 5 3 4 3 2 5 2
##  [2413] 5 1 4 1 3 1 5 3 1 2 2 4 5 4 5 5 5 4 1 2 5 3 1 1 2 2 2 5 2 2 4 1 4 5 2 1
##  [2449] 2 4 3 4 2 4 4 2 3 4 3 1 2 5 5 5 3 2 2 2 4 3 1 1 5 1 3 5 3 3 3 5 5 1 5 3
##  [2485] 4 1 5 3 4 4 5 4 2 5 2 3 4 2 2 4 1 3 1 4 2 4 3 3 2 1 1 4 3 2 4 5 4 1 5 1
##  [2521] 1 1 2 4 1 1 1 1 1 1 5 3 5 1 5 5 1 1 3 4 3 4 1 1 2 1 4 5 5 2 5 4 1 1 4 3
##  [2557] 3 3 1 2 1 5 4 4 5 5 3 3 4 5 2 1 2 4 2 3 5 5 4 4 5 2 5 5 2 5 1 4 1 2 3 4
##  [2593] 2 3 4 1 1 4 2 4 3 1 1 5 3 4 2 1 1 2 3 3 4 2 4 3 3 1 2 1 2 4 2 2 5 4 1 4
##  [2629] 1 1 4 4 3 2 1 1 5 1 1 5 2 4 1 2 5 1 1 3 1 4 1 2 5 3 5 3 5 4 3 3 4 4 5 4
##  [2665] 2 3 4 5 1 3 3 4 4 2 5 1 2 4 1 2 5 5 2 3 4 1 5 4 5 4 3 4 3 1 5 1 1 2 2 4
##  [2701] 3 4 3 2 2 1 2 3 2 1 4 2 5 2 5 2 3 3 3 5 2 1 5 2 2 3 1 5 3 5 2 4 4 4 2 3
##  [2737] 3 5 4 3 4 5 3 5 1 1 5 5 4 5 3 5 2 1 5 5 2 2 3 4 5 2 1 5 3 1 2 2 2 5 1 1
##  [2773] 1 1 4 2 1 3 4 5 5 3 2 1 2 4 3 4 4 3 2 5 5 3 4 3 5 3 3 4 1 3 4 5 5 3 2 2
##  [2809] 1 4 5 5 5 4 3 4 3 5 3 2 2 3 2 5 4 1 5 4 1 5 5 4 2 2 1 3 5 5 1 4 3 3 3 4
##  [2845] 1 2 3 2 4 1 2 5 4 4 2 4 1 2 1 5 1 3 2 1 1 4 3 2 1 2 2 1 1 5 1 3 2 4 1 5
##  [2881] 4 1 3 3 4 2 3 2 4 3 2 4 5 2 1 3 3 2 2 2 5 4 3 4 2 3 4 1 5 1 1 2 5 5 2 4
##  [2917] 4 3 1 5 2 5 1 5 3 5 4 1 5 5 2 4 5 2 5 4 5 2 3 3 4 1 1 1 5 2 3 2 1 1 1 1
##  [2953] 1 5 1 1 2 2 4 2 2 2 2 1 1 2 5 2 4 4 1 4 5 5 4 4 2 5 1 2 4 5 3 1 1 3 2 1
##  [2989] 1 3 3 4 5 5 2 2 2 1 5 3 4 5 3 5 5 3 1 5 2 5 1 5 2 3 5 4 3 1 4 5 1 3 3 4
##  [3025] 2 4 2 1 1 3 4 3 4 4 4 3 5 5 3 2 5 3 4 4 2 1 4 4 1 2 2 3 1 1 3 2 3 1 2 5
##  [3061] 2 1 2 2 4 4 4 2 2 1 5 3 5 2 3 2 1 1 1 2 4 3 3 2 3 1 4 3 4 1 2 3 1 5 3 5
##  [3097] 1 5 5 1 1 1 3 1 4 2 3 5 3 3 4 3 4 4 4 1 5 2 3 2 4 2 4 4 3 3 1 1 3 2 4 2
##  [3133] 1 3 5 1 3 4 1 1 3 4 2 3 1 2 5 4 2 4 3 4 3 2 2 5 5 5 3 4 4 5 4 5 1 5 1 2
##  [3169] 1 2 4 1 4 1 3 5 3 4 4 2 3 3 1 1 2 5 5 1 1 1 1 3 3 3 2 5 1 1 2 5 5 3 5 1
##  [3205] 2 5 5 5 4 3 4 5 1 5 5 3 1 3 1 4 1 3 2 4 3 5 3 5 5 1 5 2 5 1 4 1 5 5 3 4
##  [3241] 3 4 2 4 5 5 3 1 2 5 4 3 4 4 5 5 1 3 3 1 1 5 2 1 2 1 1 2 1 1 4 5 2 3 1 2
##  [3277] 5 1 5 1 4 1 3 5 1 2 4 3 2 1 1 2 3 3 4 2 5 3 3 2 2 5 4 5 2 4 1 5 5 1 5 5
##  [3313] 2 5 4 4 2 5 3 1 2 5 5 5 2 4 5 1 3 3 4 2 4 3 1 3 3 2 5 4 4 3 5 4 2 5 5 1
##  [3349] 1 1 5 2 3 3 5 3 1 3 1 3 5 3 2 2 2 4 5 2 3 5 1 5 4 5 1 3 4 5 1 4 1 4 5 3
##  [3385] 4 1 3 3 4 1 2 4 5 1 1 4 3 1 1 4 2 2 1 1 5 3 3 4 2 4 3 5 2 1 2 5 2 1 1 4
##  [3421] 2 2 1 2 2 3 3 2 3 1 5 2 3 5 1 1 2 3 5 5 2 4 5 1 3 1 5 4 2 1 3 3 3 2 4 5
##  [3457] 2 5 1 1 1 5 3 2 4 2 1 1 1 2 3 3 1 3 2 5 2 5 4 1 1 2 5 1 1 3 5 5 3 1 2 4
##  [3493] 4 2 5 3 4 3 2 3 2 3 5 1 1 4 1 2 3 5 1 4 3 5 2 4 1 3 1 4 4 5 4 3 3 4 1 4
##  [3529] 1 5 4 3 3 3 4 1 4 3 4 4 2 4 4 3 4 3 1 3 5 1 4 2 4 1 4 3 2 3 1 2 5 4 5 2
##  [3565] 5 5 5 1 1 2 2 3 4 4 5 5 1 3 4 2 1 1 3 5 5 3 1 3 3 4 1 1 3 5 3 3 4 5 1 3
##  [3601] 3 3 2 1 3 4 5 1 4 4 3 5 5 1 3 4 5 4 1 5 5 3 2 5 3 2 1 5 2 1 5 2 1 2 2 5
##  [3637] 2 3 2 4 1 5 5 5 5 5 3 5 1 4 3 3 4 5 5 4 4 4 3 5 4 5 5 2 3 1 1 1 2 5 1 5
##  [3673] 1 1 3 4 1 3 1 5 2 3 2 2 2 5 1 3 3 1 5 1 5 2 1 1 4 1 3 1 1 3 5 1 2 5 2 2
##  [3709] 3 5 3 3 2 1 4 3 3 5 3 4 4 5 1 5 5 5 1 3 5 3 3 1 5 5 4 3 3 4 1 4 1 4 1 2
##  [3745] 3 5 2 1 3 5 4 3 5 3 5 3 1 2 4 5 5 1 3 4 4 4 3 1 1 4 5 1 5 2 4 1 4 5 2 2
##  [3781] 1 1 3 2 5 5 3 4 2 4 2 2 5 4 5 1 5 1 2 3 4 4 2 2 4 5 5 4 2 5 2 3 2 1 5 5
##  [3817] 2 2 1 5 4 2 5 5 4 4 5 2 5 3 3 2 5 3 4 4 3 5 3 3 5 3 4 5 4 5 5 5 4 5 3 1
##  [3853] 4 2 4 1 1 5 5 4 1 4 1 4 5 5 4 5 1 2 3 3 3 3 1 2 2 4 4 5 3 5 2 1 5 1 2 2
##  [3889] 2 1 3 5 4 4 2 2 5 3 3 5 4 2 4 1 5 3 5 4 5 5 5 4 1 1 1 2 4 1 3 1 5 1 1 3
##  [3925] 3 1 5 2 3 4 5 1 1 3 1 2 3 5 4 5 5 3 2 1 3 4 3 2 4 2 5 4 2 3 1 5 4 4 5 1
##  [3961] 2 4 3 1 4 5 1 4 2 4 3 1 4 1 5 3 1 3 2 1 3 4 4 3 4 5 4 1 4 4 1 4 2 3 5 2
##  [3997] 3 5 4 5 2 1 5 4 4 3 2 1 4 5 2 4 4 2 3 4 2 4 3 4 1 5 5 2 3 3 3 5 3 1 3 3
##  [4033] 3 2 3 1 3 2 5 1 5 4 5 5 4 3 3 3 1 3 3 5 4 2 2 1 3 2 3 1 5 1 5 4 4 3 5 2
##  [4069] 5 3 1 2 4 3 3 1 3 2 4 3 2 1 5 2 1 5 1 1 1 2 4 2 2 1 1 5 5 5 5 1 4 2 4 2
##  [4105] 1 5 2 4 4 5 5 3 4 1 2 1 1 1 1 2 3 2 3 1 2 1 2 4 4 1 2 4 2 1 5 5 4 3 4 1
##  [4141] 2 4 2 4 3 5 3 5 2 5 5 3 4 2 1 5 5 5 1 4 4 3 5 2 1 1 1 4 5 3 5 4 5 5 1 4
##  [4177] 5 1 4 1 5 4 5 5 2 3 2 3 1 1 4 3 4 4 4 2 5 4 1 1 1 5 1 2 4 3 1 3 4 4 4 2
##  [4213] 4 3 4 2 1 2 2 3 3 3 3 3 4 3 4 1 4 2 1 5 5 4 1 5 1 2 3 2 2 1 3 3 5 4 3 1
##  [4249] 5 1 5 2 4 3 4 2 2 1 2 4 4 3 3 3 5 4 3 4 4 1 4 4 4 2 2 4 2 2 1 1 3 1 4 5
##  [4285] 5 4 1 1 2 3 3 3 4 4 5 5 3 4 2 1 5 1 1 5 4 5 3 3 3 3 5 4 1 4 5 2 4 2 5 2
##  [4321] 3 3 5 2 5 5 5 3 4 2 3 4 4 2 5 1 1 1 5 5 1 2 3 1 3 2 1 5 3 4 4 3 5 4 2 5
##  [4357] 5 4 5 2 5 1 5 2 4 4 4 5 5 2 2 1 1 4 4 4 3 1 3 1 1 5 1 5 2 4 2 1 2 1 5 5
##  [4393] 1 2 4 1 3 3 2 2 5 2 5 4 3 1 3 4 5 1 5 3 5 2 4 2 3 5 3 5 2 2 5 5 3 3 2 3
##  [4429] 1 5 5 2 4 3 3 5 2 2 1 1 4 2 1 4 5 2 5 4 2 4 4 1 2 2 1 5 5 4 1 3 4 1 5 2
##  [4465] 1 2 2 2 3 4 4 4 3 2 4 5 3 2 3 5 2 2 1 5 5 2 1 5 3 5 3 3 4 3 1 4 2 3 4 2
##  [4501] 4 1 1 5 1 5 1 4 2 4 1 1 3 4 1 2 5 5 4 5 4 3 4 1 1 5 1 5 4 3 5 1 4 3 2 3
##  [4537] 5 1 1 3 4 5 4 1 5 3 3 2 1 3 5 2 5 3 4 2 2 1 4 1 5 1 1 2 1 1 5 1 2 3 5 2
##  [4573] 4 1 2 2 2 4 3 2 4 5 4 3 4 2 5 1 4 1 5 4 2 3 3 5 4 4 2 4 1 4 1 3 2 4 3 5
##  [4609] 1 1 2 5 4 2 5 5 4 3 1 4 4 5 1 2 2 3 1 3 5 1 5 2 4 1 3 1 5 3 3 5 1 5 2 5
##  [4645] 5 4 4 5 2 3 4 2 3 3 4 4 4 5 3 2 5 1 2 4 1 5 3 5 3 2 2 4 1 3 2 3 1 3 5 1
##  [4681] 1 4 1 5 2 3 4 2 4 2 5 4 1 3 2 2 4 3 2 3 1 4 4 5 4 2 2 1 2 2 4 3 5 1 5 2
##  [4717] 5 2 2 4 2 3 5 2 2 2 5 2 4 3 4 1 3 5 2 5 1 4 5 1 4 3 5 5 2 1 3 3 5 5 5 2
##  [4753] 4 2 5 4 4 4 2 4 4 2 2 1 2 5 5 2 3 1 4 3 1 3 4 1 1 2 5 2 5 1 1 2 5 4 2 4
##  [4789] 2 4 4 3 1 1 1 1 5 4 2 2 1 2 2 2 3 5 5 5 5 5 4 5 2 2 5 2 3 5 4 3 5 2 5 2
##  [4825] 4 3 4 1 3 1 4 2 4 5 5 2 4 3 3 3 5 4 2 1 4 5 4 4 4 5 5 3 1 2 3 5 5 4 2 5
##  [4861] 5 4 3 3 4 5 2 1 1 1 1 2 5 4 1 4 4 2 4 2 2 3 4 1 2 1 5 4 3 2 1 3 5 5 2 3
##  [4897] 5 4 3 1 2 1 1 4 5 2 4 4 5 5 2 3 4 5 3 5 5 5 5 1 4 5 5 3 2 4 5 1 3 4 4 1
##  [4933] 1 1 3 3 1 2 3 4 4 4 5 4 4 2 4 3 2 5 1 5 5 5 3 3 3 5 5 5 5 2 4 1 4 1 2 1
##  [4969] 5 4 5 4 5 1 3 1 1 5 3 2 1 2 1 3 4 2 2 2 3 5 4 1 5 5 3 3 2 1 2 2 3 3 5 3
##  [5005] 2 4 3 3 5 5 1 4 4 2 2 1 5 4 1 5 1 3 3 1 2 5 5 2 3 5 5 4 5 3 5 5 5 1 2 5
##  [5041] 3 1 4 4 4 2 3 3 5 2 2 5 2 3 2 3 4 1 2 3 3 2 4 5 3 1 2 2 2 5 1 4 4 1 4 1
##  [5077] 1 4 1 4 5 2 4 2 3 1 4 4 1 4 1 2 3 3 5 3 2 4 3 3 2 5 5 3 2 3 3 4 5 2 2 3
##  [5113] 4 2 5 4 5 1 2 3 5 2 3 5 2 2 3 3 1 3 2 5 2 1 4 4 1 5 2 5 4 3 3 1 4 1 1 3
##  [5149] 2 4 2 1 5 1 2 3 2 5 5 5 4 3 5 3 4 4 3 3 1 2 5 2 4 5 3 1 4 4 4 4 3 4 2 4
##  [5185] 3 1 2 2 5 1 1 2 2 2 5 5 1 3 4 3 5 5 3 1 4 1 2 5 5 4 3 4 3 5 2 3 3 1 4 4
##  [5221] 1 1 3 2 5 2 5 2 3 4 4 3 2 5 5 2 3 1 1 5 4 3 5 3 4 4 2 4 2 5 3 3 3 5 3 5
##  [5257] 4 1 4 2 4 2 3 2 2 5 4 4 1 3 5 3 3 2 4 5 2 1 1 5 1 2 2 2 5 1 4 3 2 4 3 5
##  [5293] 1 3 5 1 5 4 2 1 3 1 2 5 4 3 3 4 2 4 2 2 1 2 4 4 5 5 5 5 4 1 2 2 4 2 1 2
##  [5329] 1 5 3 2 1 2 3 4 2 5 2 5 3 4 2 5 2 1 1 4 4 2 1 5 1 2 4 1 2 1 3 2 2 4 2 4
##  [5365] 4 1 3 3 3 5 2 1 5 3 4 2 2 3 5 1 3 5 4 3 3 4 4 2 2 3 3 2 5 1 5 4 5 4 1 1
##  [5401] 5 2 4 5 4 1 4 2 5 1 3 2 4 1 4 3 1 1 5 2 4 2 2 5 4 5 3 5 3 3 3 5 1 4 1 4
##  [5437] 2 4 3 5 2 2 5 1 1 3 2 5 4 3 3 5 2 4 5 2 3 1 1 3 5 1 4 3 2 1 2 1 3 4 4 3
##  [5473] 1 5 5 2 1 3 1 5 2 1 2 4 4 1 4 4 5 5 4 1 5 2 2 4 3 1 5 1 5 4 1 4 5 2 5 2
##  [5509] 2 2 5 5 2 3 2 4 1 3 2 1 3 5 4 5 4 5 2 1 3 4 3 5 5 4 1 2 1 4 3 3 2 5 5 5
##  [5545] 3 4 4 5 1 4 1 4 5 5 2 4 1 1 5 5 1 5 1 3 1 3 1 3 5 4 2 2 1 3 5 5 1 4 2 3
##  [5581] 4 3 5 5 5 3 2 3 4 5 1 4 2 1 1 1 3 3 5 2 4 1 1 5 4 5 3 1 5 2 4 5 3 3 3 4
##  [5617] 5 1 3 3 5 1 4 3 5 5 1 3 4 3 4 3 3 1 3 5 2 2 4 4 1 4 2 4 1 4 1 2 4 1 5 2
##  [5653] 1 3 5 1 2 4 4 5 2 2 3 5 4 5 2 2 5 3 4 2 5 5 5 4 2 1 3 4 5 2 1 1 2 1 2 3
##  [5689] 2 2 5 1 5 5 4 3 3 2 3 5 5 3 1 3 2 5 1 3 1 5 4 5 4 5 5 2 5 3 4 4 3 5 5 4
##  [5725] 4 3 1 2 5 2 2 1 1 3 1 5 2 5 4 2 5 1 2 4 1 1 2 5 3 3 5 4 5 2 1 1 4 4 1 5
##  [5761] 5 1 1 4 1 2 4 1 3 1 3 2 4 2 3 2 4 2 4 2 3 5 5 1 3 4 4 4 3 2 2 2 2 5 3 3
##  [5797] 5 5 5 5 2 1 5 2 4 2 2 3 5 4 2 3 3 3 1 5 1 5 2 3 1 3 2 2 4 4 2 3 4 3 1 4
##  [5833] 3 2 1 1 1 1 5 3 5 2 2 1 1 1 5 1 4 2 1 3 5 3 1 4 4 1 1 3 1 2 1 1 1 4 3 2
##  [5869] 2 3 5 3 4 4 5 1 5 3 2 2 3 4 4 3 4 5 1 3 4 2 2 2 5 3 4 4 4 3 5 4 3 4 4 3
##  [5905] 5 5 4 4 3 1 1 1 5 3 2 2 1 4 2 4 1 5 5 5 1 4 4 2 1 4 5 4 2 3 2 5 5 5 2 2
##  [5941] 1 2 1 4 2 2 2 5 1 1 1 4 3 2 3 3 2 4 3 1 5 2 3 3 2 4 5 3 2 4 3 3 4 4 3 5
##  [5977] 2 3 1 2 3 2 3 1 5 3 5 5 4 5 5 4 1 5 5 3 1 4 3 1 5 2 4 2 5 2 4 2 3 4 3 4
##  [6013] 1 5 3 3 1 4 3 1 5 4 4 2 3 2 1 4 5 4 2 5 3 4 5 4 1 2 4 4 2 4 1 4 5 2 4 1
##  [6049] 5 3 5 2 3 5 2 2 5 1 4 4 5 1 3 3 2 5 4 4 2 2 3 3 1 3 4 4 5 4 5 2 3 1 5 5
##  [6085] 4 5 5 3 5 3 4 5 5 3 2 4 5 2 5 5 2 4 4 5 4 5 1 2 2 1 1 5 1 4 1 5 4 1 5 5
##  [6121] 5 5 1 4 1 1 5 4 3 3 4 5 3 4 3 5 4 4 4 1 4 4 2 2 4 3 2 3 5 2 2 2 1 3 2 3
##  [6157] 3 3 2 5 5 5 4 3 5 2 4 5 1 4 5 5 5 1 3 3 1 5 3 5 3 2 4 2 2 4 4 4 3 1 5 5
##  [6193] 4 3 2 3 2 3 3 1 2 5 5 5 3 2 4 4 5 5 1 3 4 5 4 5 4 2 3 4 3 4 3 1 3 5 5 2
##  [6229] 4 1 2 3 2 4 4 3 4 4 5 4 2 3 5 2 2 5 4 2 3 4 4 3 5 1 5 2 1 5 3 2 3 5 3 1
##  [6265] 4 4 5 4 4 1 5 3 4 5 4 1 3 2 1 1 3 1 5 4 3 1 2 1 3 4 4 1 3 4 3 1 4 3 4 3
##  [6301] 4 3 1 5 5 3 4 2 4 5 4 3 3 1 2 4 4 2 2 4 2 1 3 4 3 5 2 1 5 5 5 4 1 1 2 5
##  [6337] 1 5 2 5 3 3 4 2 3 2 2 1 2 2 5 3 1 2 5 3 3 1 4 3 2 3 5 1 1 3 1 1 2 5 2 4
##  [6373] 2 4 4 1 2 5 3 3 5 1 4 2 5 5 2 1 4 2 5 5 4 5 4 3 5 4 3 2 4 3 5 5 4 2 4 3
##  [6409] 5 3 5 3 1 2 2 2 4 1 3 2 4 2 1 5 5 4 3 3 1 1 1 5 4 4 3 1 5 5 4 3 5 3 2 4
##  [6445] 2 2 4 5 1 3 1 1 1 3 2 4 3 1 4 2 4 2 2 2 1 1 3 1 3 1 1 5 2 4 4 4 5 1 5 3
##  [6481] 1 1 2 2 4 5 2 5 4 1 5 5 2 4 4 3 1 2 4 2 5 4 3 4 4 4 3 4 3 3 1 1 5 3 3 4
##  [6517] 4 2 5 5 4 5 2 3 4 5 2 5 3 1 2 4 1 2 5 4 4 4 5 1 2 2 5 5 4 5 3 4 3 3 3 4
##  [6553] 1 1 2 4 5 2 4 3 4 3 5 1 1 5 1 1 5 1 3 4 3 3 1 2 1 5 1 4 1 1 1 3 2 2 4 1
##  [6589] 4 3 1 5 2 1 3 1 5 5 5 3 5 2 5 1 2 3 4 5 1 5 2 3 5 5 2 3 3 3 3 4 4 3 5 5
##  [6625] 4 1 1 2 3 2 2 2 5 5 5 3 4 2 3 3 5 3 4 2 4 3 4 3 5 3 5 2 4 5 5 3 1 5 5 1
##  [6661] 2 1 1 3 3 1 5 1 1 5 5 4 1 1 3 3 4 5 4 3 4 1 1 3 1 2 2 5 5 1 4 4 3 4 3 1
##  [6697] 5 2 5 2 5 3 5 1 5 4 5 5 5 5 1 1 3 4 1 4 3 5 1 5 2 3 2 1 3 5 4 1 3 3 2 4
##  [6733] 1 4 5 1 4 4 5 5 1 3 4 3 3 5 3 2 2 2 1 1 1 3 3 3 2 4 5 3 5 2 4 4 1 3 5 4
##  [6769] 2 5 4 2 2 3 4 1 4 3 1 1 4 2 3 1 2 4 4 4 2 3 3 5 1 2 3 5 2 2 3 4 5 2 5 3
##  [6805] 3 1 3 1 5 5 4 5 5 3 3 5 4 4 3 4 2 5 5 4 2 5 2 1 4 5 2 4 1 2 1 1 2 2 4 4
##  [6841] 1 4 2 5 2 3 5 5 3 5 4 3 2 4 5 2 5 1 2 4 4 2 2 2 3 2 5 3 4 4 3 5 2 2 4 5
##  [6877] 3 1 4 3 1 3 5 4 5 1 3 1 1 3 2 5 3 2 5 1 5 1 4 2 3 3 2 2 3 4 5 2 4 3 1 3
##  [6913] 2 5 5 5 3 1 1 3 3 2 2 2 4 4 4 3 4 4 1 1 5 3 3 2 1 3 3 2 5 1 1 5 5 5 4 3
##  [6949] 3 3 1 4 2 1 3 3 5 4 3 4 4 5 1 4 1 4 1 5 1 2 5 2 4 4 4 2 3 3 2 3 2 4 2 2
##  [6985] 3 3 1 2 5 1 5 5 3 3 2 3 1 5 5 5 1 4 4 2 1 1 2 3 1 2 4 3 5 1 2 5 3 3 1 4
##  [7021] 2 3 4 4 3 4 4 1 2 5 3 4 3 5 4 3 5 3 3 2 5 1 1 1 3 5 2 5 2 2 4 3 4 4 1 3
##  [7057] 2 5 1 2 5 5 5 5 5 5 3 3 1 1 2 1 1 4 4 3 5 1 2 4 3 1 1 5 2 2 3 1 5 5 1 1
##  [7093] 5 3 5 3 4 1 4 5 3 4 3 2 5 5 2 5 1 3 3 2 2 4 1 1 4 4 1 2 3 5 2 3 3 4 2 5
##  [7129] 1 5 3 3 3 1 5 1 5 2 2 1 4 3 1 5 1 4 5 1 3 5 1 3 2 1 1 3 4 2 3 4 3 3 5 2
##  [7165] 3 5 3 1 4 5 2 5 3 3 5 4 1 1 3 2 2 2 3 1 2 2 2 4 4 1 3 2 4 5 5 2 1 5 1 3
##  [7201] 3 5 2 5 3 5 3 5 3 4 4 2 2 1 2 3 5 5 1 2 2 2 5 3 2 5 5 4 3 4 5 1 5 3 2 1
##  [7237] 4 1 4 3 1 2 1 1 4 2 3 1 2 4 4 3 2 3 3 1 4 5 4 2 3 4 5 4 3 3 1 2 3 4 1 4
##  [7273] 1 2 4 4 5 4 3 4 2 5 4 2 1 1 3 4 2 5 4 5 3 3 4 4 1 2 3 3 2 3 1 1 2 4 2 1
##  [7309] 1 4 1 5 4 1 2 3 4 4 3 2 4 5 4 1 3 4 2 5 2 5 1 2 1 1 2 5 2 1 3 1 3 1 2 5
##  [7345] 3 5 4 2 4 5 3 2 3 3 3 1 1 3 5 4 1 1 5 4 2 5 2 3 2 4 5 4 2 2 2 5 1 2 1 1
##  [7381] 1 5 5 3 5 3 3 1 1 5 4 5 4 2 2 5 4 5 5 3 3 4 1 1 5 3 4 4 5 2 3 2 4 5 5 3
##  [7417] 5 1 1 5 5 1 5 3 3 5 3 3 1 1 4 2 5 1 5 4 1 5 4 1 2 5 4 1 3 1 3 3 1 4 3 4
##  [7453] 3 3 5 3 4 2 2 2 2 3 3 5 3 2 5 3 1 2 4 3 3 1 4 2 1 5 2 4 1 3 4 5 3 2 3 2
##  [7489] 1 1 2 4 2 4 2 2 5 2 2 4 2 4 4 2 4 4 4 3 3 5 4 1 2 2 1 2 1 1 3 1 4 1 1 4
##  [7525] 3 2 5 3 1 5 1 5 3 1 3 5 3 4 5 3 2 2 1 4 3 2 5 5 3 4 3 1 1 2 1 5 5 3 1 2
##  [7561] 2 2 5 2 2 3 1 5 1 5 1 2 2 5 5 4 5 1 3 4 3 2 4 1 3 4 5 1 2 3 3 1 5 3 5 3
##  [7597] 5 2 2 4 3 3 2 4 2 5 5 1 4 5 5 3 5 4 4 3 2 4 5 1 2 4 5 5 3 3 5 3 3 4 5 4
##  [7633] 4 4 3 4 1 3 1 4 4 2 1 5 3 2 2 1 1 1 1 1 4 2 5 1 3 2 2 4 1 5 3 1 1 2 2 1
##  [7669] 2 1 2 3 1 4 5 3 1 5 4 5 1 3 4 2 5 3 2 1 3 4 5 5 2 1 2 4 3 3 3 5 1 1 3 3
##  [7705] 1 3 2 4 3 2 4 4 1 1 4 3 4 5 5 2 2 3 1 2 4 5 3 1 4 1 4 1 5 5 2 3 3 5 1 4
##  [7741] 5 3 3 1 3 1 3 1 2 1 3 5 5 4 4 4 4 5 2 2 3 4 1 1 3 1 4 2 5 3 2 2 2 1 2 1
##  [7777] 5 1 3 2 2 2 2 3 1 5 1 2 4 2 3 2 3 4 1 5 1 5 4 3 3 1 2 1 2 5 1 3 5 5 5 2
##  [7813] 4 5 5 1 3 1 5 5 2 1 2 2 3 5 5 3 3 3 2 1 1 1 2 2 5 5 2 2 1 5 5 1 4 4 1 2
##  [7849] 4 2 3 2 1 3 1 1 3 2 4 5 1 5 4 2 3 2 5 3 1 1 5 3 1 2 1 4 3 5 2 3 1 3 3 2
##  [7885] 4 4 2 4 4 2 1 2 5 4 3 4 2 1 3 1 4 5 4 1 5 4 4 4 2 5 1 4 5 3 2 4 5 1 1 1
##  [7921] 4 5 5 4 2 2 3 4 2 4 5 2 5 3 5 5 4 1 1 3 5 2 1 5 2 4 2 1 1 4 2 3 5 3 2 1
##  [7957] 2 5 2 4 3 3 3 4 5 3 4 2 3 4 1 4 4 5 5 1 1 5 1 3 3 1 1 3 5 3 3 3 3 3 2 3
##  [7993] 1 1 1 1 4 2 4 1 4 2 3 5 2 1 2 5 5 3 2 2 3 5 5 3 3 5 5 5 3 4 5 5 5 1 4 1
##  [8029] 2 5 3 5 5 2 3 2 4 4 4 4 2 4 2 4 5 3 4 1 5 5 2 3 5 5 5 4 1 2 1 4 4 3 2 3
##  [8065] 1 5 4 2 2 2 4 1 1 5 1 1 2 1 1 2 2 5 3 2 4 2 2 3 5 3 5 2 2 4 3 5 1 1 5 3
##  [8101] 1 3 4 4 2 1 4 3 5 2 2 2 4 3 4 2 3 1 3 5 4 5 4 1 1 3 3 3 4 3 1 5 1 3 2 1
##  [8137] 5 2 1 3 3 1 5 1 1 2 2 5 5 5 4 4 3 4 1 5 2 4 2 3 2 3 2 2 4 4 3 2 4 5 2 1
##  [8173] 2 1 2 3 4 2 5 2 1 5 3 1 2 4 5 2 4 2 4 2 3 2 5 1 1 5 4 2 1 5 3 1 3 3 5 2
##  [8209] 5 1 3 2 2 3 3 3 2 2 3 5 5 4 3 5 3 3 3 2 2 1 2 5 2 3 1 2 3 2 1 4 3 2 5 1
##  [8245] 4 5 2 2 3 2 3 4 2 5 5 4 2 1 4 4 1 3 2 2 4 5 5 1 5 3 2 5 5 4 4 4 4 4 5 1
##  [8281] 4 4 2 3 4 1 1 3 4 2 2 4 1 2 4 5 2 3 3 4 5 3 4 4 4 5 3 5 1 2 2 3 5 2 5 3
##  [8317] 3 2 4 3 4 3 4 5 4 5 1 4 4 5 1 1 1 4 4 5 1 5 1 2 3 4 5 1 3 3 3 4 5 4 3 1
##  [8353] 2 4 5 5 3 1 5 4 4 1 3 1 1 5 5 2 2 1 1 2 1 3 2 4 3 2 2 4 4 5 3 1 2 4 5 3
##  [8389] 4 1 2 2 2 2 4 2 3 3 2 2 4 4 3 2 1 4 3 3 1 3 4 4 1 2 4 1 4 1 1 2 5 1 2 1
##  [8425] 3 2 4 1 1 1 3 2 1 3 4 4 3 4 2 3 5 5 4 2 1 1 2 3 5 1 3 3 1 1 5 2 5 3 4 5
##  [8461] 5 4 5 4 5 4 2 4 5 1 1 3 5 3 3 1 3 1 2 4 4 1 5 4 3 5 5 1 5 4 4 3 5 1 4 1
##  [8497] 5 3 1 1 1 3 4 1 5 3 4 4 3 3 3 4 1 2 5 5 2 2 2 1 2 3 3 2 1 4 2 5 5 4 2 2
##  [8533] 3 3 4 5 1 4 5 1 1 2 1 1 4 4 4 3 2 5 2 2 4 3 3 4 2 5 5 5 1 1 5 1 3 2 3 5
##  [8569] 5 3 4 2 4 5 3 5 3 2 3 3 3 1 3 4 5 3 1 3 2 2 1 3 2 5 1 4 4 2 1 4 2 2 1 4
##  [8605] 4 5 2 4 2 4 4 5 4 3 1 4 4 1 2 5 3 2 3 2 2 2 2 2 4 5 3 1 4 2 4 2 4 2 5 3
##  [8641] 3 2 3 1 2 4 5 2 4 1 4 4 4 2 3 5 1 5 5 5 1 4 3 4 1 5 1 4 5 5 1 4 3 5 3 2
##  [8677] 5 5 2 2 1 2 5 2 1 5 2 5 1 1 4 1 5 4 2 3 4 5 4 3 4 2 3 4 3 2 2 5 3 5 5 5
##  [8713] 2 4 5 4 5 1 1 2 2 5 5 5 1 1 3 4 3 2 3 1 4 3 1 4 1 4 1 2 5 2 1 5 3 1 3 1
##  [8749] 1 4 4 2 4 4 4 2 1 4 1 4 4 3 3 4 4 5 4 1 5 5 2 1 1 1 3 1 2 3 2 4 2 3 5 3
##  [8785] 3 5 2 4 5 3 5 4 2 5 5 3 2 5 2 3 3 3 4 4 4 3 1 1 4 1 2 4 1 2 3 1 4 2 1 5
##  [8821] 4 2 5 4 5 1 3 4 2 5 5 5 2 4 1 1 4 5 3 5 2 3 4 1 4 4 3 2 3 3 2 3 1 5 2 1
##  [8857] 4 3 5 4 4 1 3 2 5 1 5 5 3 2 1 3 3 2 2 1 2 4 1 5 5 5 3 2 4 3 2 2 4 4 3 5
##  [8893] 3 5 2 2 1 5 3 4 5 5 2 1 2 2 2 3 2 3 2 4 5 1 4 4 3 3 4 4 3 4 2 4 2 1 4 2
##  [8929] 5 4 4 2 5 4 1 5 1 5 2 2 2 5 5 2 3 1 3 3 1 2 4 1 2 3 2 4 5 5 4 3 2 5 2 4
##  [8965] 1 5 5 1 3 4 4 1 2 5 2 4 3 1 1 2 3 3 5 2 3 4 4 3 1 2 3 2 5 2 2 5 3 2 4 3
##  [9001] 1 4 2 4 3 4 3 5 4 3 5 3 1 5 4 1 4 3 2 1 5 2 1 5 5 2 4 2 3 3 4 5 5 2 2 5
##  [9037] 5 1 5 4 2 3 4 4 3 2 4 1 1 4 2 5 1 1 3 3 3 1 3 4 2 1 4 3 5 4 1 4 5 3 3 1
##  [9073] 3 4 5 5 2 2 5 2 3 1 5 4 4 4 2 3 1 1 5 3 3 1 3 4 2 2 3 2 5 2 1 3 3 5 4 5
##  [9109] 4 2 3 1 3 1 5 3 2 1 3 3 1 5 5 5 4 5 4 5 3 3 2 5 3 5 3 4 5 3 1 2 4 2 1 4
##  [9145] 1 5 4 4 4 1 4 4 5 1 4 4 2 1 5 4 1 2 3 5 5 1 1 4 3 2 5 5 1 5 5 1 1 2 5 4
##  [9181] 3 4 3 3 3 5 3 5 2 1 5 5 2 3 4 3 5 4 5 4 3 4 5 5 1 3 1 3 3 4 4 4 4 3 3 5
##  [9217] 1 4 3 3 3 2 1 3 5 5 3 1 3 1 1 4 3 4 4 4 4 2 5 1 5 2 3 5 5 4 1 3 1 5 5 3
##  [9253] 4 2 3 1 2 2 5 5 5 5 4 2 3 1 5 5 2 1 4 5 4 4 2 3 3 5 3 3 5 5 4 2 3 2 4 2
##  [9289] 4 3 1 5 1 5 2 4 2 5 2 2 2 4 3 4 1 2 2 5 5 2 1 2 2 2 5 5 4 4 1 2 3 1 1 2
##  [9325] 4 5 1 2 3 1 4 2 2 4 4 1 3 4 5 4 1 4 3 1 1 2 1 5 1 4 5 4 2 4 4 4 4 3 3 3
##  [9361] 3 4 1 3 2 3 2 3 1 4 2 3 5 3 4 5 2 4 5 3 3 5 1 2 4 5 4 1 3 1 4 2 5 2 4 3
##  [9397] 2 5 1 1 2 5 3 2 1 2 2 2 4 2 1 5 1 2 1 4 3 4 1 2 1 4 2 3 1 5 5 4 1 4 5 3
##  [9433] 4 4 5 1 3 4 5 2 4 2 2 4 1 1 3 1 5 4 2 3 1 5 3 5 5 5 2 1 5 1 5 3 4 5 5 3
##  [9469] 5 5 2 4 2 1 2 1 1 3 3 2 4 1 5 1 4 1 1 5 4 5 5 2 4 2 1 3 5 1 3 1 1 1 5 2
##  [9505] 4 4 2 4 2 2 5 3 4 3 5 3 3 3 3 2 4 5 5 5 5 2 2 3 4 5 4 1 5 2 2 3 5 3 2 1
##  [9541] 3 5 4 1 4 2 5 4 2 3 2 4 2 1 2 1 5 5 1 2 2 4 2 2 4 4 5 2 5 2 5 3 4 4 3 4
##  [9577] 4 3 3 1 2 4 2 1 4 2 1 5 3 3 2 3 2 2 3 1 3 4 4 3 5 2 5 4 2 5 5 1 1 5 1 4
##  [9613] 3 3 2 2 2 4 5 5 1 4 4 3 2 3 3 4 3 3 5 4 4 1 5 2 3 3 2 1 5 5 3 3 5 1 2 2
##  [9649] 4 2 3 5 4 2 1 4 1 1 5 5 4 4 3 5 5 2 5 2 5 1 3 2 2 2 2 5 5 1 4 2 3 3 1 3
##  [9685] 3 2 4 4 2 4 4 5 2 4 3 5 3 2 3 4 3 3 2 5 4 3 4 2 3 3 5 5 5 4 1 3 3 1 2 1
##  [9721] 4 5 3 4 5 3 3 4 2 1 5 1 3 4 2 4 4 1 4 1 1 2 4 3 2 4 1 5 5 3 4 5 3 4 1 1
##  [9757] 5 3 1 4 5 1 1 3 1 1 1 5 5 3 2 1 2 2 4 3 4 3 2 5 1 2 4 3 3 2 3 3 3 4 3 1
##  [9793] 3 3 1 3 2 3 2 1 1 3 3 5 5 3 5 1 1 2 1 1 1 3 4 1 3 1 2 5 4 1 3 1 1 4 2 3
##  [9829] 4 3 5 5 1 5 4 1 3 3 5 5 1 1 4 2 5 1 5 1 4 1 5 2 4 1 5 4 1 5 4 2 1 3 1 5
##  [9865] 2 3 1 3 4 5 4 3 1 3 1 4 2 3 4 4 2 1 2 3 2 2 1 4 4 2 4 1 2 4 3 1 2 3 1 2
##  [9901] 3 1 4 2 5 2 5 2 5 3 3 4 1 2 2 2 1 3 5 2 4 5 2 1 3 3 2 5 3 4 1 3 3 4 1 2
##  [9937] 1 4 4 2 3 5 5 1 4 5 4 3 3 4 1 5 2 1 3 3 4 2 5 3 1 5 1 2 3 5 2 2 1 5 4 3
##  [9973] 1 1 5 3 1 1 3 3 4 3 5 1 2 3 2 4 5 4 3 3 2 5 1 4 1 3 1 3 3 5 5 5 1 3 5 4
## [10009] 1 3 4 2 5 1 4 3 5 5 3 2 4 2 1 2 1 2 1 2 1 3 5 2 4 3 5 4 5 1 1 4 2 2 4 2
## [10045] 2 5 2 1 1 1 4 5 5 4 2 2 4 1 4 5 4 2 5 5 2 3 2 2 2 5 3 3 4 5 1 1 5 3 4 5
## [10081] 1 1 4 5 3 3 1 5 1 1 2 5 4 4 1 4 4 3 2 4 3 1 4 3 5 3 5 1 5 5 3 1 2 2 3 3
## [10117] 3 5 4 1 5 4 2 1 3 5 5 1 3 5 2 3 3 2 5 2 1 3 5 3 1 3 3 4 2 1 4 1 3 1 3 2
## [10153] 2 5 4 2 3 4 3 5 5 4 4 2 2 3 1 3 2 1 2 4 1 2 3 1 5 5 5 1 1 2 1 3 2 5 3 1
## [10189] 2 3 2 4 1 2 4 3 1 5 5 5 2 5 4 3 4 5 1 4 5 4 2 1 2 4 4 3 5 1 1 4 4 2 4 1
## [10225] 1 1 1 1 3 2 1 3 5 2 2 1 2 5 1 3 3 1 1 2 3 3 4 4 2 1 4 4 2 2 3 1 1 4 3 5
## [10261] 3 5 5 1 4 5 4 5 2 2 1 1 4 2 2 1 5 4 1 3 5 2 5 1 1 3 3 5 3 2 1 1 1 1 1 2
## [10297] 1 2 3 3 5 2 5 5 2 5 3 4 4 2 4 1 4 2 5 4 1 4 5 1 5 3 1 5 5 3 5 2 3 2 4 1
## [10333] 4 5 3 5 4 2 5 4 3 4 4 2 5 5 2 2 5 4 4 2 3 5 5 1 4 1 5 5 2 2 3 3 5 5 2 2
## [10369] 1 3 1 2 5 4 3 3 2 4 2 5 3 4 4 1 1 3 4 1 1 1 3 3 3 4 1 5 4 3 4 2 3 3 1 2
## [10405] 3 3 4 2 3 2 1 4 2 4 3 4 3 4 5 5 1 4 3 2 4 3 3 3 4 2 5 3 5 2 1 2 4 1 2 4
## [10441] 1 5 3 5 2 2 3 3 4 2 3 1 2 5 4 4 2 5 1 5 4 5 4 3 1 2 3 2 5 3 3 1 5 1 3 5
## [10477] 2 5 4 1 5 3 2 1 5 5 2 3 4 4 2 2 5 1 4 3 4 2 3 4 3 4 3 2 1 3 1 2 5 3 2 2
## [10513] 5 2 4 3 1 5 1 5 3 3 4 1 1 3 5 3 5 2 3 2 1 2 4 3 5 2 2 2 5 4 5 1 4 4 2 4
## [10549] 2 1 4 1 2 5 2 1 2 1 2 1 3 3 3 3 2 4 2 2 5 5 3 4 1 5 4 3 2 5 5 3 1 3 2 1
## [10585] 4 2 4 4 5 5 1 5 2 3 1 3 1 4 5 1 3 3 2 5 4 2 1 3 1 1 2 5 2 5 2 2 1 5 3 3
## [10621] 2 2 4 5 4 3 2 5 2 5 2 1 5 2 5 2 5 3 1 3 2 1 3 5 5 2 5 3 2 5 4 1 5 5 5 1
## [10657] 5 4 3 2 5 1 5 3 5 1 3 3 1 3 5 3 3 4 5 1 5 1 4 3 1 3 3 1 4 1 2 5 5 5 5 4
## [10693] 5 1 3 4 1 3 4 2 5 4 4 1 4 1 2 4 5 1 1 5 1 2 2 4 2 4 4 3 5 5 4 2 2 3 4 3
## [10729] 1 4 4 3 1 2 1 4 3 2 5 1 5 4 1 2 3 2 2 5 5 2 4 5 4 4 3 5 5 4 1 2 5 2 1 3
## [10765] 4 5 5 5 2 1 4 3 1 4 3 1 3 2 4 3 1 4 1 3 3 2 4 1 2 3 2 1 1 1 3 2 5 1 4 5
## [10801] 4 3 2 5 5 2 1 1 2 4 1 4 4 3 2 2 1 3 2 4 1 5 5 3 3 1 5 1 5 1 4 4 5 1 4 2
## [10837] 4 1 5 4 1 5 4 4 1 4 5 5 2 1 2 3 5 2 3 1 1 1 1 4 4 4 1 3 4 3 5 2 3 1 2 2
## [10873] 3 1 3 1 4 3 4 5 3 2 3 2 2 3 3 5 5 1 4 5 3 5 2 1 5 1 3 4 4 3 4 3 5 1 3 2
## [10909] 3 2 4 5 3 4 4 1 5 1 5 4 1 3 4 5 4 1 2 3 4 4 5 1 4 2 4 4 2 5 5 2 4 3 2 4
## [10945] 1 5 2 1 5 4 2 2 4 5 2 4 5 5 1 5 4 2 5 3 5 1 2 3 2 5 1 2 1 2 3 1 2 5 3 4
## [10981] 4 1 2 3 1 2 4 3 1 3 2 3 3 1 2 2 3 2 1 2 5 3 1 5 4 2 4 1 1 3 4 1 1 5 2 4
## [11017] 5 3 5 2 2 1 5 4 3 1 3 4 2 1 3 1 3 1 3 2 2 5 3 1 5 5 4 4 3 5 2 2 4 2 1 1
## [11053] 5 5 4 3 1 5 3 4 4 3 3 5 3 3 4 5 4 4 4 3 5 2 5 4 3 3 2 1 3 5 5 3 1 4 2 4
## [11089] 5 3 4 4 4 3 5 1 5 3 1 1 1 2 5 1 2 1 1 5 2 3 5 3 5 5 2 2 1 3 4 5 4 2 4 3
## [11125] 2 5 1 3 2 2 3 3 3 3 2 4 1 5 4 5 5 2 5 2 3 2 5 3 1 1 4 3 2 1 2 2 4 4 4 2
## [11161] 3 1 3 4 2 3 1 5 3 3 3 1 3 4 5 1 5 5 4 5 2 4 1 3 4 4 1 5 5 4 4 2 4 2 1 5
## [11197] 5 5 2 4 2 2 2 3 1 3 4 1 2 2 3 5 1 3 1 1 4 5 4 4 2 3 2 1 5 4 1 5 3 2 4 2
## [11233] 4 3 5 1 3 2 4 1 2 5 2 3 5 2 1 3 2 2 4 1 3 2 1 3 3 4 1 1 3 1 5 2 1 3 5 2
## [11269] 5 4 3 5 4 5 2 1 3 2 2 2 1 4 4 5 5 1 2 2 3 4 3 1 5 4 1 2 1 2 3 4 4 3 2 4
## [11305] 3 4 2 1 3 3 3 1 1 5 2 1 2 4 5 1 1 3 1 4 3 1 1 2 3 1 1 3 5 2 4 3 1 4 3 4
## [11341] 3 3 2 1 5 5 1 5 3 3 2 1 4 1 1 4 4 2 1 2 3 1 2 3 1 3 5 3 3 3 4 5 3 2 1 5
## [11377] 4 2 3 2 1 3 3 5 4 3 3 2 1 2 5 2 2 5 2 1 5 1 5 1 1 4 4 1 2 5 2 4 1 4 3 4
## [11413] 3 4 3 5 1 5 1 5 2 2 5 5 4 5 5 1 2 4 3 1 4 5 1 4 5 5 2 5 3 5 2 4 4 3 3 5
## [11449] 2 5 3 5 1 3 5 1 4 4 4 1 1 5 1 5 2 5 4 3 5 4 3 1 5 1 1 3 2 4 1 2 5 4 2 3
## [11485] 1 2 1 5 3 5 3 4 3 2 2 5 2 1 1 2 1 1 1 5 4 3 4 5 1 4 1 4 5 1 2 4 4 2 5 1
## [11521] 4 1 3 1 5 2 2 2 4 1 2 3 4 5 4 5 2 5 3 4 1 2 4 3 1 3 1 1 1 1 1 4 4 1 1 5
## [11557] 1 3 5 5 5 2 1 4 2 3 3 5 1 5 5 5 4 3 5 4 5 5 5 4 4 4 5 1 2 2 4 5 2 3 5 3
## [11593] 2 5 3 2 5 1 2 3 3 5 5 4 2 1 3 4 3 1 1 4 1 1 2 3 5 5 3 4 1 1 4 3 1 3 3 1
## [11629] 1 1 5 3 3 4 1 1 1 1 1 2 5 3 2 4 2 1 2 2 3 3 3 3 2 5 4 4 3 5 3 5 3 2 2 1
## [11665] 1 4 2 2 4 3 4 2 3 5 5 3 3 1 2 5 1 5 2 3 1 5 5 1 4 2 1 2 2 3 1 1 4 3 5 1
## [11701] 5 1 3 2 4 1 5 3 4 1 4 2 3 3 1 5 5 3 3 5 5 1 4 4 4 1 5 3 1 4 5 5 3 4 2 3
## [11737] 4 2 2 5 1 4 5 3 5 1 3 5 4 4 3 4 3 1 1 5 1 5 1 2 1 2 4 2 1 1 3 2 3 3 5 2
## [11773] 5 4 5 2 4 2 3 1 1 3 5 5 3 5 1 4 3 5 3 1 1 3 3 1 2 3 3 5 1 5 5 4 5 1 2 2
## [11809] 3 4 3 2 4 5 4 4 1 4 5 3 2 3 3 3 2 2 2 5 1 5 1 4 1 3 5 1 4 2 4 3 4 1 4 1
## [11845] 2 1 1 2 2 1 2 4 1 1 2 5 2 2 5 2 4 1 3 2 2 5 1 3 1 1 1 5 4 5 3 4 5 2 2 4
## [11881] 4 3 5 1 5 3 3 5 3 2 5 1 2 3 3 2 2 3 1 4 5 1 1 1 1 2 2 3 1 4 3 1 2 3 4 2
## [11917] 5 5 5 4 4 3 1 1 1 5 2 5 3 3 5 5 2 3 5 5 1 5 3 2 2 2 4 1 3 4 1 1 3 4 3 5
## [11953] 4 2 1 3 1 5 5 1 2 3 2 3 3 4 2 5 3 5 4 5 2 1 5 2 2 3 1 5 2 1 5 2 4 4 1 4
## [11989] 1 1 4 3 1 1 2 2 3 4 4 4 4 5 2 2 2 3 3 3 5 2 5 4 2 2 3 4 5 2 1 2 2 1 2 4
## [12025] 2 3 3 4 1 3 4 5 2 1 5 4 5 4 2 5 5 2 5 1 3 1 5 2 3 3 4 4 4 4 2 2 4 1 4 4
## [12061] 2 2 2 4 1 5 1 4 5 1 1 4 1 5 2 5 1 3 4 5 5 1 3 1 3 3 2 1 4 4 5 3 4 1 5 4
## [12097] 5 3 4 5 1 4 5 1 4 4 3 1 3 4 2 1 1 2 3 1 1 5 4 3 1 5 4 3 2 4 4 4 5 5 4 1
## [12133] 5 3 1 4 2 3 4 1 2 4 1 3 2 5 3 1 1 1 5 2 3 2 1 3 5 4 4 5 1 1 1 5 4 1 2 2
## [12169] 3 3 4 1 4 2 1 3 5 1 5 3 1 1 5 4 2 4 2 1 1 1 4 2 2 4 1 5 1 1 4 3 1 4 4 1
## [12205] 4 1 4 4 5 5 2 4 2 4 2 1 5 2 3 2 3 3 4 4 5 2 4 5 1 5 5 1 4 2 1 4 3 2 3 3
## [12241] 2 3 1 2 3 3 5 3 3 5 5 1 2 3 4 2 2 2 5 2 1 3 4 5 3 1 5 3 2 1 1 5 1 2 2 4
## [12277] 2 2 5 3 3 1 5 1 4 2 3 2 4 3 5 5 2 5 1 5 4 1 5 2 5 5 4 1 4 1 1 4 1 1 3 2
## [12313] 5 1 2 4 1 5 5 5 4 5 2 3 4 2 5 3 3 5 5 1 1 1 3 1 2 3 4 2 2 4 5 2 1 1 5 3
## [12349] 1 3 5 5 1 1 5 3 4 4 1 5 5 4 5 5 1 3 3 3 5 4 2 4 2 5 5 4 4 3 1 1 3 1 3 5
## [12385] 2 3 3 1 2 1 5 4 3 2 2 5 1 1 2 2 2 2 2 5 3 1 1 2 1 3 3 5 1 2 4 5 2 3 3 5
## [12421] 4 1 1 5 2 1 1 3 5 5 1 1 3 1 1 1 4 1 1 1 4 1 1 2 5 4 2 2 4 2 3 5 1 5 4 3
## [12457] 2 5 5 1 1 3 4 5 5 4 1 5 5 2 3 2 3 3 3 2 5 1 4 1 1 5 4 4 5 2 2 4 2 4 3 5
## [12493] 2 1 4 2 1 2 4 3 5 3 5 5 2 3 1 1 2 5 5 2 2 3 4 4 3 4 2 2 5 5 5 2 4 2 3 3
## [12529] 4 5 5 5 4 5 3 3 2 4 2 1 5 2 3 5 5 5 1 4 3 3 5 4 2 5 3 2 2 3 4 3 1 5 2 1
## [12565] 1 4 2 5 2 5 1 5 1 3 5 4 1 5 4 3 5 5 3 5 2 3 4 1 1 1 4 1 4 4 1 4 3 5 3 3
## [12601] 3 3 4 5 5 3 3 1 3 3 3 3 3 2 4 3 4 2 5 3 3 4 3 4 3 1 2 3 5 5 5 3 5 4 3 3
## [12637] 1 2 5 2 4 2 4 2 3 4 4 3 3 1 2 4 4 4 1 1 3 2 3 1 1 3 5 5 3 1 5 2 1 1 1 4
## [12673] 4 4 1 2 2 1 5 5 2 4 3 4 2 3 4 5 1 4 1 4 5 1 2 1 5 5 4 4 2 4 5 3 5 2 5 3
## [12709] 4 3 4 5 4 3 4 2 5 4 4 3 4 4 5 5 1 5 2 5 1 2 5 2 4 3 3 2 2 4 3 4 3 1 3 5
## [12745] 5 4 4 3 5 2 1 3 5 1 2 1 5 2 1 3 3 5 2 4 2 4 3 1 1 5 4 5 3 1 3 3 4 4 1 1
## [12781] 2 4 4 3 3 5 2 4 2 2 2 1 3 3 5 5 2 4 5 3 2 4 1 3 3 4 3 1 2 4 5 1 3 1 1 2
## [12817] 2 1 3 5 4 4 3 2 5 5 4 1 2 1 2 4 1 2 4 5 2 1 1 3 5 5 1 2 3 5 5 4 4 1 4 2
## [12853] 1 1 4 3 5 5 4 5 5 1 1 2 3 2 5 3 1 3 3 3 4 4 2 2 2 4 5 5 1 4 2 2 1 4 4 5
## [12889] 2 5 4 4 3 2 1 3 5 3 3 4 2 2 5 5 1 4 5 1 4 5 5 3 1 5 3 5 5 2 3 5 1 2 5 3
## [12925] 3 2 5 2 4 5 1 2 4 4 3 1 3 2 3 3 3 5 2 3 5 4 1 4 2 5 5 5 3 1 2 3 1 1 4 1
## [12961] 5 2 4 1 4 4 1 5 5 5 4 4 2 5 5 1 4 3 3 4 1 3 2 4 5 1 3 5 4 1 1 2 4 2 4 3
## [12997] 5 2 4 1 1 1 4 3 2 1 5 1 5 2 4 2 5 3 1 2 3 4 2 1 3 2 3 3 1 5 1 2 4 2 1 1
## [13033] 5 3 1 3 3 2 4 4 4 5 5 3 3 5 3 3 5 5 1 1 4 5 5 2 1 4 1 2 2 1 1 2 3 4 2 2
## [13069] 1 1 1 1 2 3 1 3 3 5 4 4 2 3 5 4 5 4 2 4 1 4 1 2 2 2 4 5 2 3 4 1 4 4 1 4
## [13105] 3 4 4 4 4 5 3 1 5 3 4 2 5 3 3 5 3 3 3 3 2 1 5 3 4 5 1 4 3 2 3 3 3 3 2 5
## [13141] 1 4 3 3 1 4 4 2 2 1 3 3 2 2 3 3 4 1 2 4 4 1 2 4 2 1 2 1 1 5 1 5 4 2 5 2
## [13177] 1 1 3 5 1 2 1 3 3 5 4 3 2 4 5 5 1 2 4 3 4 2 5 5 5 5 4 5 3 4 3 2 5 3 3 3
## [13213] 1 1 2 5 4 1 1 3 1 5 4 3 4 3 2 4 4 4 5 1 3 4 2 4 1 5 1 2 2 2 2 3 1 2 1 5
## [13249] 4 5 2 5 1 2 2 3 1 2 5 1 2 4 3 3 2 4 2 1 1 2 2 4 4 2 2 2 4 5 3 2 5 3 2 2
## [13285] 2 4 1 5 1 3 4 2 5 1 1 3 2 2 4 5 2 1 2 5 5 5 3 1 3 3 1 1 4 1 1 2 2 1 1 2
## [13321] 3 3 2 2 2 2 4 2 3 5 5 5 4 5 1 5 5 3 5 5 4 2 3 4 3 2 4 3 3 5 1 2 4 4 3 3
## [13357] 3 1 4 1 2 1 4 4 1 5 2 3 1 3 1 4 4 4 5 1 2 4 5 4 1 3 4 4 5 4 2 2 4 1 5 5
## [13393] 2 2 5 2 3 1 2 2 1 1 5 5 1 4 3 4 5 5 3 3 1 4 3 5 2 3 5 1 2 3 3 1 1 2 2 4
## [13429] 4 5 2 3 4 2 3 5 4 1 1 1 2 5 3 2 2 4 4 2 2 1 1 5 4 5 5 4 2 5 3 5 1 3 1 1
## [13465] 5 2 2 2 3 5 5 5 3 4 2 4 3 4 3 4 1 4 4 1 1 3 1 5 2 1 1 1 1 2 5 5 3 2 3 4
## [13501] 1 5 5 2 2 2 2 3 2 4 3 2 4 5 2 3 2 4 5 1 2 1 1 2 3 3 4 1 3 1 1 5 3 1 3 1
## [13537] 3 4 3 3 2 4 2 1 4 5 3 5 1 5 3 1 4 3 3 4 2 2 1 4 2 5 5 3 3 4 4 5 1 2 4 2
## [13573] 5 4 4 4 1 1 5 5 2 4 5 1 3 2 3 2 1 3 4 4 3 5 5 3 4 4 1 1 1 5 1 2 2 4 4 1
## [13609] 3 5 2 5 3 5 2 5 5 1 4 1 2 4 4 1 5 3 5 4 4 3 2 2 1 5 3 1 4 5 3 4 1 3 2 3
## [13645] 5 4 4 1 4 2 1 5 4 3 3 2 2 1 3 2 5 5 1 1 5 5 1 1 1 3 2 5 4 1 4 5 1 5 5 4
## [13681] 2 4 2 2 3 3 2 1 1 1 1 5 4 5 4 3 2 2 4 4 5 1 1 5 5 1 4 5 1 5 2 5 1 2 1 2
## [13717] 3 3 1 2 2 2 1 3 4 4 5 2 5 4 3 1 2 1 5 3 5 3 1 5 5 4 5 2 4 4 4 5 4 3 5 2
## [13753] 4 1 2 2 2 1 3 3 2 5 3 2 5 4 4 4 4 2 3 2 4 5 5 3 3 5 3 2 3 5 4 1 3 1 2 3
## [13789] 3 3 5 3 5 4 5 2 2 5 1 2 2 2 2 3 4 1 1 5 1 3 3 1 3 1 3 1 3 3 2 5 4 4 2 1
## [13825] 2 3 1 1 5 1 3 1 2 1 5 5 5 1 5 3 3 1 4 1 2 2 5 2 1 1 5 5 4 2 4 5 2 4 3 3
## [13861] 1 3 1 5 2 4 3 1 2 3 3 2 5 3 3 1 5 4 4 1 2 4 5 3 5 2 1 2 1 2 2 4 1 5 5 5
## [13897] 3 4 1 3 2 4 4 3 4 1 1 5 2 2 4 1 5 1 1 1 5 3 5 5 5 5 5 4 5 2 3 4 1 4 2 5
## [13933] 5 4 4 2 5 3 2 5 4 1 5 3 5 4 3 2 3 2 5 1 1 1 1 4 1 3 5 3 2 5 2 5 5 4 5 1
## [13969] 1 2 1 3 1 1 1 1 3 1 5 3 4 4 4 5 2 2 5 2 3 5 5 4 2 1 1 3 1 2 3 5 1 1 3 3
## [14005] 1 2 2 1 4 5 4 3 1 1 4 1 1 3 2 1 2 3 5 1 1 4 1 2 5 3 1 1 2 4 4 2 5 4 5 4
## [14041] 4 2 4 3 3 5 2 2 4 1 4 1 5 3 4 5 5 2 3 1 2 3 3 5 3 1 1 2 3 2 3 4 5 3 5 5
## [14077] 5 4 2 1 2 3 3 2 5 5 3 1 2 3 3 5 5 4 1 5 5 3 1 1 4 3 4 2 5 3 4 5 2 4 3 4
## [14113] 5 4 2 1 2 4 4 2 4 5 5 3 5 2 2 5 2 2 4 2 1 5 1 5 2 3 3 4 4 2 1 5 1 3 3 3
## [14149] 3 1 5 5 4 5 5 5 4 2 3 5 2 3 4 1 4 5 5 5 3 4 5 2 4 2 2 4 5 1 1 5 1 3 1 1
## [14185] 2 4 5 3 4 2 3 1 1 3 3 4 1 5 4 1 1 3 2 5 5 3 1 1 4 3 1 1 2 5 1 5 3 1 1 2
## [14221] 4 4 4 2 3 2 1 2 2 2 5 5 3 1 3 2 1 3 3 5 4 4 5 2 4 1 2 4 4 1 3 1 3 4 3 1
## [14257] 2 2 3 3 4 1 4 2 3 5 3 3 2 4 1 4 1 1 1 2 2 2 1 3 4 3 4 3 3 3 5 4 3 4 4 3
## [14293] 3 2 4 4 4 5 3 5 4 1 5 5 3 2 3 2 4 4 4 2 3 4 1 4 1 3 5 5 4 1 2 1 3 1 5 3
## [14329] 2 2 1 5 2 3 1 2 3 1 3 2 4 1 1 2 4 2 2 2 2 1 3 3 4 1 5 4 2 5 2 3 1 2 2 2
## [14365] 5 3 4 4 4 4 3 1 3 2 1 3 4 5 2 1 3 3 5 5 1 1 5 4 2 3 2 2 4 2 2 3 2 1 3 2
## [14401] 3 5 2 4 2 5 4 5 1 4 3 2 3 2 2 3 5 5 5 4 3 2 4 5 4 5 3 4 5 4 2 3 5 4 4 5
## [14437] 2 5 5 1 1 1 4 1 1 1 4 5 5 5 2 3 2 2 1 2 5 4 2 2 4 2 1 2 3 5 4 1 1 5 4 5
## [14473] 3 1 1 5 1 5 1 1 5 5 1 3 3 4 4 5 1 3 3 3 5 4 3 4 2 2 1 4 4 1 5 1 2 5 4 3
## [14509] 4 2 5 5 3 5 4 3 4 3 2 5 1 3 2 4 5 1 3 1 2 2 1 1 2 3 1 4 1 4 5 4 1 4 2 4
## [14545] 1 2 5 5 5 1 5 4 2 2 4 4 1 5 2 4 5 3 1 1 3 1 3 1 2 1 4 3 5 2 2 1 1 2 3 2
## [14581] 3 5 4 4 5 1 5 4 4 5 2 2 2 1 3 5 5 2 3 4 1 1 1 1 4 2 5 3 2 4 3 3 4 4 1 1
## [14617] 3 3 3 5 1 1 4 3 4 3 5 5 2 4 1 4 4 4 2 1 3 2 1 1 2 5 1 2 5 3 3 5 5 2 1 4
## [14653] 5 5 2 5 5 3 4 2 4 3 1 1 3 3 3 1 2 2 2 4 2 4 5 3 4 3 1 3 2 4 1 2 4 3 1 5
## [14689] 2 1 2 4 1 1 5 3 1 5 5 5 2 2 1 2 3 2 3 3 1 5 5 4 2 3 5 1 4 4 5 3 1 1 1 2
## [14725] 1 4 4 4 1 4 1 2 1 5 1 1 3 4 1 3 5 1 4 3 2 5 1 1 2 1 4 3 4 2 4 5 1 5 4 2
## [14761] 2 5 4 2 4 1 2 2 4 2 1 2 3 1 5 5 3 5 3 1 1 1 1 5 1 4 5 1 2 1 1 3 4 4 4 2
## [14797] 1 5 1 1 3 5 1 4 5 1 3 1 3 3 1 1 3 3 4 3 2 4 5 2 4 3 1 5 1 4 5 5 4 3 5 3
## [14833] 3 5 3 4 4 2 3 1 1 2 2 5 5 4 5 4 1 2 2 1 4 1 1 3 2 4 2 1 3 1 5 1 1 3 3 4
## [14869] 4 5 4 4 5 1 4 2 3 4 4 5 2 2 4 2 4 4 1 2 5 3 3 2 2 3 5 5 4 4 1 2 2 3 1 4
## [14905] 4 4 3 5 2 1 3 5 1 4 1 5 2 2 5 1 3 3 1 3 5 5 4 1 2 4 4 3 3 3 5 5 3 5 2 5
## [14941] 3 4 2 4 3 1 5 2 1 3 2 4 3 5 5 1 2 2 5 2 1 5 5 5 4 4 2 2 2 5 1 4 1 3 4 4
## [14977] 2 5 1 2 4 4 1 2 4 4 2 1 2 4 3 2 3 1 3 5 4 4 4 1 5 1 3 3 3 1 1 1 4 4 1 1
## [15013] 2 2 5 1 5 1 4 1 1 2 1 2 1 5 5 1 5 2 1 2 4 3 1 4 1 1 1 3 4 5 5 5 2 1 2 5
## [15049] 2 3 5 4 4 5 2 1 4 1 2 2 3 1 5 1 3 4 5 1 4 2 3 5 2 2 4 3 5 1 3 5 1 5 1 2
## [15085] 5 3 4 2 3 2 2 2 3 4 1 3 4 4 2 5 5 2 1 1 3 3 2 2 1 2 4 5 1 2 5 4 4 2 3 4
## [15121] 1 2 1 3 3 5 2 1 5 5 1 4 3 4 1 4 4 4 1 2 4 2 3 1 1 3 2 5 3 3 5 3 3 4 1 4
## [15157] 5 4 1 3 5 5 2 3 2 3 3 2 4 2 4 3 1 3 1 5 4 3 1 5 5 4 4 1 4 3 4 1 3 3 2 2
## [15193] 4 3 3 5 3 4 4 2 1 5 2 3 5 3 5 5 2 2 1 5 5 1 4 4 5 1 3 5 2 5 2 2 5 4 4 5
## [15229] 5 2 5 1 2 1 3 5 1 4 1 2 5 3 5 1 3 5 3 1 2 1 4 3 3 4 3 3 2 2 3 3 3 5 2 2
## [15265] 1 3 4 5 3 3 5 4 3 2 3 5 3 1 4 1 5 1 3 1 2 5 5 3 3 2 4 1 3 2 2 3 3 5 5 5
## [15301] 3 3 1 2 5 4 1 3 2 2 4 2 5 1 5 5 2 2 2 5 3 5 1 3 3 2 2 1 1 4 2 5 5 1 1 5
## [15337] 4 4 1 4 1 4 3 5 2 1 3 4 3 3 2 1 3 1 2 4 5 3 4 2 2 4 1 3 4 5 3 5 5 2 1 3
## [15373] 1 3 1 3 1 2 1 5 4 2 3 4 2 2 3 2 4 5 1 2 4 5 5 2 2 2 2 2 4 5 4 2 1 1 2 4
## [15409] 4 1 5 4 1 3 4 3 5 5 1 5 1 1 5 4 3 4 4 1 5 2 1 5 5 5 1 3 3 4 5 3 1 5 2 5
## [15445] 2 4 3 5 2 3 1 4 5 1 3 2 4 5 4 2 2 1 3 4 3 2 5 5 3 3 3 5 2 3 2 5 4 5 2 3
## [15481] 4 1 5 4 3 5 4 3 4 2 1 3 2 3 5 1 5 2 5 5 1 3 5 5 5 3 3 3 3 2 2 3 1 1 2 4
## [15517] 1 5 1 5 4 2 1 5 1 2 1 1 1 3 3 1 2 4 3 5 2 1 4 5 4 2 4 4 5 3 1 4 2 5 3 2
## [15553] 1 5 3 1 5 4 3 3 3 2 5 2 3 1 5 4 4 4 1 4 4 4 2 5 3 2 5 2 1 4 4 4 3 5 4 3
## [15589] 5 1 4 3 1 2 5 4 5 3 1 3 5 3 1 5 1 2 2 4 2 1 3 1 3 4 1 5 5 5 5 2 4 2 3 3
## [15625] 2 5 1 3 4 1 2 1 3 5 2 1 1 1 3 2 4 5 5 2 3 2 4 5 4 3 1 5 4 3 2 3 2 2 4 1
## [15661] 1 1 1 5 1 2 4 2 3 5 3 3 2 1 4 5 5 4 1 3 3 5 4 2 4 2 1 4 2 3 5 4 4 5 4 5
## [15697] 4 1 2 5 1 3 3 2 5 3 1 3 2 3 3 3 1 1 1 4 4 2 3 3 4 1 3 3 3 5 1 1 5 3 4 4
## [15733] 3 2 4 5 3 3 5 4 5 2 1 3 3 3 3 2 3 2 3 1 4 2 3 2 3 4 4 3 1 5 3 3 4 1 1 2
## [15769] 1 4 3 1 5 1 1 5 2 5 3 2 1 3 3 5 1 4 1 5 2 5 2 1 5 4 4 3 4 1 2 3 2 5 5 4
## [15805] 3 1 1 4 2 5 4 1 3 2 3 2 5 2 1 1 3 5 1 4 3 3 1 4 2 4 1 1 2 4 1 3 5 1 2 5
## [15841] 4 1 5 4 5 1 5 3 4 3 2 3 1 4 3 5 5 4 5 3 3 3 3 4 4 2 1 3 1 2 4 5 4 1 2 5
## [15877] 3 1 4 2 2 2 5 4 4 1 2 2 3 4 2 1 1 3 4 2 5 4 3 5 3 5 4 5 2 4 2 3 1 1 3 5
## [15913] 4 1 1 4 1 1 2 4 4 1 1 5 4 2 5 3 3 2 4 2 2 5 3 3 3 4 2 5 3 2 2 2 4 2 3 3
## [15949] 1 5 3 4 1 4 3 2 2 4 2 4 4 5 2 5 2 2 2 2 3 4 5 5 2 4 5 1 1 2 3 1 1 2 1 1
## [15985] 4 1 2 4 4 4 1 4 1 3 4 1 4 3 5 1 4 1 2 1 2 4 4 3 2 5 5 5 1 3 4 4 4 5 3 4
## [16021] 4 1 5 2 1 3 4 2 2 2 1 5 2 2 2 1 5 2 5 1 4 5 2 3 4 4 2 1 4 2 5 4 3 2 5 2
## [16057] 1 3 3 1 5 5 4 5 3 3 3 1 5 2 5 3 4 2 2 2 1 1 3 4 3 4 5 4 3 4 5 3 2 1 2 5
## [16093] 3 3 1 4 1 5 2 1 5 2 5 5 1 2 4 5 3 3 1 3 1 1 3 4 4 3 3 1 5 5 5 5 3 2 1 5
## [16129] 3 4 5 3 3 5 2 1 2 2 5 3 3 2 4 2 2 4 2 5 4 4 2 3 3 5 1 5 4 5 3 1 1 1 1 4
## [16165] 1 1 4 5 2 5 1 4 1 4 3 2 4 2 4 1 2 5 5 3 2 1 5 2 4 5 1 4 5 1 1 2 4 4 1 5
## [16201] 5 1 1 4 5 4 2 2 1 2 2 4 5 4 5 3 5 4 3 3 3 4 3 4 2 4 3 2 1 2 4 4 4 1 5 5
## [16237] 1 1 2 1 5 1 2 2 4 2 3 5 1 3 5 2 5 4 5 3 3 5 2 2 2 1 3 2 3 5 4 1 5 5 1 2
## [16273] 5 3 5 5 5 2 2 1 3 2 2 2 3 5 5 1 5 1 2 5 3 4 3 1 1 3 2 2 1 1 2 3 2 5 2 3
## [16309] 2 3 3 4 1 2 1 2 4 4 2 3 4 4 5 4 1 1 2 4 1 2 1 1 1 2 1 5 4 2 2 1 4 4 3 3
## [16345] 4 4 1 2 3 1 3 3 5 5 1 4 5 3 1 1 5 2 3 1 4 5 3 1 5 4 2 1 1 5 3 4 4 5 2 4
## [16381] 1 1 2 3 5 2 2 2 4 3 1 4 3 5 1 5 1 4 2 5 3 4 2 4 4 2 3 4 2 5 2 1 4 5 4 5
## [16417] 2 1 1 2 5 2 2 2 5 5 1 4 1 5 4 2 5 5 5 1 2 4 4 5 5 3 2 4 2 4 5 3 4 3 5 3
## [16453] 4 4 1 5 2 4 1 2 3 3 5 3 1 1 1 5 1 5 3 1 1 4 2 1 1 2 3 2 1 2 4 2 1 3 4 3
## [16489] 2 2 4 4 2 4 5 5 2 2 5 2 2 4 2 3 5 1 2 3 2 5 3 1 2 4 3 3 1 2 5 1 3 4 5 3
## [16525] 5 5 2 3 2 2 1 2 4 2 1 4 4 5 5 2 2 4 2 1 4 5 4 1 5 1 4 2 2 5 5 5 2 5 3 5
## [16561] 5 1 3 1 3 2 2 1 4 1 2 2 4 1 2 5 5 5 5 4 3 4 3 5 3 4 5 5 5 2 5 5 4 5 2 2
## [16597] 3 5 4 4 2 5 3 4 3 2 4 1 5 4 2 2 3 2 2 4 2 4 5 2 3 1 4 3 5 4 5 3 5 4 5 5
## [16633] 5 5 2 5 2 4 5 2 2 3 2 2 3 3 4 3 5 1 2 4 3 1 4 1 2 1 3 2 4 1 5 2 5 5 4 4
## [16669] 2 5 4 1 1 5 4 2 1 2 5 4 3 2 4 3 2 5 4 4 5 5 3 5 2 4 2 2 5 2 2 2 2 5 4 5
## [16705] 4 3 3 5 2 4 4 1 1 1 1 1 3 5 3 5 4 2 1 1 2 5 2 2 2 3 2 3 2 1 3 2 5 4 5 3
## [16741] 4 2 2 2 4 5 4 4 3 2 1 4 3 5 4 5 3 5 3 3 1 4 1 2 1 1 4 3 3 4 5 1 3 2 1 5
## [16777] 4 3 3 4 2 2 1 3 1 5 2 5 5 3 2 2 1 2 4 5 5 1 4 4 5 4 5 3 3 4 5 3 4 5 1 1
## [16813] 1 4 4 1 4 2 5 5 5 1 2 2 1 5 1 4 2 1 1 2 5 2 3 2 3 3 5 4 2 3 3 4 5 4 4 5
## [16849] 2 1 3 2 3 5 1 1 1 4 5 5 5 1 2 1 2 5 1 2 3 1 5 1 3 2 2 2 4 1 4 2 3 5 5 4
## [16885] 3 2 1 5 1 5 3 4 3 4 5 2 4 2 2 1 4 2 2 4 5 4 4 3 4 1 3 5 3 4 2 5 5 5 1 2
## [16921] 4 1 2 1 2 4 5 4 2 2 2 3 3 3 1 1 1 1 1 5 2 3 4 2 4 3 2 2 1 5 5 4 1 3 1 2
## [16957] 4 4 1 3 3 1 1 2 5 1 1 1 1 5 3 1 1 3 1 4 3 5 5 3 4 1 2 2 5 2 4 4 3 1 2 5
## [16993] 3 5 3 3 5 1 2 1 4 1 1 4 5 2 2 3 2 1 2 1 3 4 5 1 3 4 4 4 2 1 2 2 2 1 3 5
## [17029] 1 2 4 3 5 1 2 3 1 5 1 3 4 5 1 4 4 2 4 2 2 5 5 1 5 1 1 1 4 5 1 1 3 2 5 1
## [17065] 3 3 5 4 4 5 5 4 2 1 2 4 3 5 3 5 1 1 2 5 3 4 5 4 5 1 5 5 3 4 4 5 1 5 5 5
## [17101] 5 1 3 2 5 1 2 3 2 5 1 2 3 2 1 4 5 2 4 4 1 3 4 5 3 1 4 3 1 4 2 1 2 4 2 1
## [17137] 1 2 4 5 4 3 4 5 4 5 3 3 5 1 1 3 1 5 4 2 4 2 5 1 4 2 3 3 5 1 5 3 4 5 4 2
## [17173] 1 4 1 4 3 3 4 3 2 4 3 3 5 1 2 1 1 2 1 3 5 4 1 2 1 2 1 2 1 1 3 2 5 2 1 1
## [17209] 1 2 4 5 1 2 4 3 3 3 5 1 3 2 1 5 3 2 3 4 3 5 3 3 1 5 3 2 1 3 1 1 4 1 1 2
## [17245] 1 1 3 4 3 1 1 1 3 2 1 5 4 5 5 5 5 3 5 3 5 3 1 3 1 3 5 3 1 2 1 5 3 3 4 1
## [17281] 3 5 1 3 2 3 3 5 1 1 2 2 1 2 3 4 5 2 2 3 5 4 5 5 2 3 3 5 4 2 4 3 4 5 3 4
## [17317] 3 4 1 2 3 4 3 4 3 1 4 4 1 3 4 4 4 1 4 4 4 3 1 2 5 3 5 5 5 5 2 2 3 1 2 3
## [17353] 1 5 4 3 1 4 2 2 5 1 4 5 4 5 5 3 2 5 1 1 1 1 3 5 3 4 5 2 2 3 3 4 1 4 5 3
## [17389] 3 4 3 4 4 1 4 5 1 3 2 5 4 4 1 1 1 5 4 4 4 2 5 2 3 4 1 2 5 2 1 4 3 5 2 3
## [17425] 2 3 3 1 5 2 2 3 4 3 3 3 2 1 5 1 5 3 4 4 2 2 2 3 3 1 1 5 5 5 2 3 5 2 5 4
## [17461] 4 1 4 1 5 1 3 2 2 4 1 5 5 3 4 4 4 4 2 4 1 2 1 4 5 3 1 5 1 4 3 3 1 5 4 3
## [17497] 3 4 2 5 3 1 1 5 3 3 5 4 1 2 1 1 1 5 5 3 5 5 1 5 2 2 3 3 4 4 4 4 2 5 4 1
## [17533] 2 1 4 2 5 4 5 3 3 3 1 3 1 5 4 2 1 1 1 5 4 5 2 5 4 1 3 4 3 3 3 5 4 1 3 1
## [17569] 2 1 5 2 5 2 1 4 3 2 2 2 5 4 3 2 4 3 2 3 4 1 3 5 3 4 5 5 1 4 3 5 1 5 4 3
## [17605] 4 3 2 1 3 1 3 5 4 4 1 2 3 4 1 3 2 3 4 1 4 1 2 1 5 2 2 3 1 2 3 2 1 2 3 2
## [17641] 3 2 1 3 4 1 4 2 1 3 3 3 2 2 4 2 2 4 5 1 4 2 1 4 3 1 2 1 1 4 3 1 2 2 1 2
## [17677] 3 4 5 2 5 5 5 5 3 3 5 3 5 4 4 5 4 2 3 1 3 4 5 2 2 2 2 3 2 4 2 2 4 2 4 4
## [17713] 4 5 3 2 2 5 2 2 4 2 4 5 4 3 2 4 3 3 2 2 5 4 2 1 5 3 2 1 4 4 5 3 4 1 5 4
## [17749] 5 5 1 2 2 5 4 4 4 4 3 4 1 3 1 2 2 2 5 3 5 2 2 1 2 3 1 3 5 1 3 1 2 3 5 3
## [17785] 1 4 5 5 4 5 5 2 1 4 1 3 4 3 4 2 2 4 5 3 3 2 3 2 2 3 5 4 2 4 5 5 1 2 3 4
## [17821] 3 3 3 1 2 1 1 4 5 3 3 4 3 5 2 1 4 2 2 1 4 2 2 1 2 3 1 4 5 2 1 5 1 5 5 5
## [17857] 2 3 5 3 5 2 4 4 5 1 5 4 5 5 3 4 1 1 1 2 4 4 4 5 2 1 1 3 2 5 2 5 2 5 4 2
## [17893] 2 1 4 2 1 5 1 1 1 2 3 2 5 1 1 3 2 3 1 1 2 5 2 3 3 5 1 1 5 4 4 5 1 5 3 1
## [17929] 3 4 4 5 4 3 1 3 5 3 2 1 3 1 1 3 5 3 1 1 4 4 2 2 4 4 3 3 5 1 4 5 4 2 2 3
## [17965] 1 3 2 5 4 3 4 5 5 4 5 3 3 4 5 5 4 1 4 4 4 1 1 1 4 3 3 3 2 1 5 2 3 3 2 3
## [18001] 3 5 4 1 5 1 4 5 2 5 3 5 4 2 3 2 3 5 1 3 1 5 4 5 1 4 3 1 4 4 5 1 2 5 3 2
## [18037] 4 4 5 4 4 3 1 2 1 2 5 3 1 1 4 3 4 3 1 3 3 1 5 4 1 2 1 2 4 1 5 2 2 2 5 4
## [18073] 1 4 3 4 3 3 3 4 1 1 4 5 1 3 1 3 3 3 1 3 5 3 5 4 4 3 4 1 4 2 3 1 5 3 4 4
## [18109] 5 5 2 2 5 5 4 2 5 3 1 5 2 5 1 3 1 5 5 3 1 3 1 2 1 2 1 5 1 3 3 1 5 4 2 2
## [18145] 5 5 1 2 3 5 4 4 3 2 3 5 3 1 1 3 4 2 1 1 3 5 4 2 2 1 4 3 4 2 4 3 1 5 4 5
## [18181] 2 2 4 1 2 4 3 2 4 1 4 4 2 1 4 3 4 4 4 1 5 2 4 4 5 3 3 5 1 5 5 1 4 5 3 3
## [18217] 2 2 3 2 1 4 4 5 4 3 2 5 5 4 1 5 1 5 5 2 1 3 2 4 4 1 1 4 1 5 1 3 4 3 2 4
## [18253] 3 4 5 2 5 1 3 3 5 1 1 2 3 3 4 2 1 4 1 5 3 2 2 2 3 3 4 2 5 5 4 4 4 2 4 2
## [18289] 3 5 5 5 5 4 3 2 3 3 1 5 5 1 5 1 3 3 2 4 5 3 5 2 4 1 1 2 2 5 1 4 3 1 4 1
## [18325] 2 3 5 1 5 3 2 5 4 5 5 5 2 2 1 2 4 4 1 1 1 2 4 4 2 2 1 3 4 3 5 5 2 2 2 1
## [18361] 5 3 4 1 2 2 2 2 1 3 1 4 3 5 3 4 2 3 4 2 3 2 1 1 4 1 5 2 2 1 5 3 4 5 4 2
## [18397] 1 5 2 3 2 1 3 3 1 1 5 2 2 3 5 3 4 3 3 2 5 4 1 5 5 2 2 4 3 1 4 2 5 1 4 4
## [18433] 4 5 2 3 1 2 2 5 2 1 5 4 3 5 2 5 3 4 2 1 2 1 1 4 4 4 4 4 4 4 1 4 4 3 4 1
## [18469] 3 3 5 5 2 2 3 4 5 4 5 3 2 5 3 5 5 1 1 4 5 2 3 3 2 4 5 3 1 2 3 3 1 3 5 1
## [18505] 3 1 1 2 1 5 4 1 2 5 2 1 1 1 3 5 1 5 1 4 1 1 5 3 2 3 4 4 5 4 2 5 2 2 2 5
## [18541] 3 5 1 3 4 5 1 3 5 1 2 5 5 4 4 4 1 4 1 4 5 4 3 5 3 3 2 1 5 3 2 5 2 1 5 3
## [18577] 4 5 4 4 2 4 3 4 2 3 4 3 2 1 2 4 1 1 1 5 2 4 3 5 3 2 5 3 5 1 2 2 3 4 5 5
## [18613] 4 5 1 2 4 1 2 1 2 3 2 5 2 2 5 2 4 5 5 2 5 4 4 2 3 4 4 1 2 2 3 5 4 2 4 1
## [18649] 4 5 3 3 3 3 1 5 2 4 2 5 3 5 4 2 3 5 3 3 2 5 4 3 3 5 1 4 3 1 5 3 5 5 2 4
## [18685] 4 1 3 5 2 5 5 3 1 2 2 4 2 1 2 2 5 3 2 5 3 4 5 2 3 4 4 5 1 3 4 3 3 1 1 3
## [18721] 3 1 5 3 2 1 5 5 2 3 3 2 4 1 2 1 2 3 3 1 2 5 2 1 3 1 5 2 1 2 1 2 5 1 3 1
## [18757] 1 3 4 5 5 4 5 2 3 3 5 5 4 5 2 3 3 1 4 2 5 2 1 3 4 4 4 3 4 3 2 3 3 1 3 3
## [18793] 3 1 5 5 4 3 2 4 3 1 5 5 4 2 2 5 2 5 5 2 5 3 5 5 5 4 4 1 4 2 2 2 5 3 4 5
## [18829] 5 4 3 2 2 5 2 5 5 4 1 3 5 2 4 1 3 3 4 3 1 5 2 2 5 4 1 2 5 1 5 3 2 1 5 2
## [18865] 2 3 2 4 1 1 4 1 3 2 5 5 3 1 5 3 3 5 1 4 5 3 4 1 4 5 2 4 2 5 2 1 2 4 4 2
## [18901] 3 5 5 5 3 4 5 1 2 2 4 4 2 3 2 3 4 2 5 4 3 5 1 3 1 5 5 3 2 4 2 2 5 2 1 4
## [18937] 5 1 1 3 2 3 2 5 1 3 1 1 2 3 5 2 1 4 2 1 4 4 2 5 4 5 1 1 4 2 2 4 3 2 5 3
## [18973] 2 2 5 4 5 3 5 5 5 2 2 2 5 3 4 3 5 3 3 5 5 3 2 2 3 4 1 5 1 4 3 5 5 3 1 1
## [19009] 3 2 4 1 5 1 1 4 5 3 5 2 1 2 5 2 2 3 2 4 4 1 1 3 5 5 5 5 3 2 4 4 4 3 2 4
## [19045] 3 4 2 3 4 3 1 5 3 2 1 3 2 3 3 4 2 4 1 4 3 2 3 5 5 1 2 4 2 5 2 1 4 4 2 1
## [19081] 5 4 5 2 4 3 2 2 3 1 1 3 2 1 2 4 1 1 5 3 3 4 1 2 3 4 4 3 3 1 3 4 5 4 1 2
## [19117] 3 5 1 1 2 1 2 2 2 4 5 3 1 4 2 5 2 3 1 3 4 5 4 1 4 1 4 5 5 3 1 3 2 4 4 4
## [19153] 5 4 2 3 3 2 3 3 2 4 5 3 5 2 4 2 4 4 3 2 1 5 5 4 1 5 1 4 3 2 5 2 3 3 2 1
## [19189] 3 2 1 2 4 4 1 5 1 2 1 2 5 1 4 4 2 4 4 5 5 5 4 4 5 1 4 4 1 3 1 2 2 3 5 3
## [19225] 5 1 5 1 1 4 2 4 3 5 5 5 1 4 1 1 3 5 4 1 1 2 1 2 2 5 3 2 5 3 5 5 2 3 3 3
## [19261] 5 1 4 1 3 1 1 3 1 4 2 4 1 3 1 4 5 2 3 4 5 2 1 3 4 3 2 2 5 1 1 3 3 3 1 5
## [19297] 5 4 5 3 2 4 5 3 4 2 4 1 5 2 4 1 1 5 1 1 4 1 2 4 1 3 3 3 4 3 4 2 5 4 5 5
## [19333] 3 2 2 3 4 1 2 3 3 2 4 3 3 2 1 2 2 1 4 2 2 3 2 4 3 3 4 3 1 2 5 5 4 5 2 5
## [19369] 3 3 1 5 5 2 2 4 1 1 5 2 3 4 2 5 2 4 1 3 2 3 4 2 1 5 5 3 4 1 1 3 3 2 5 4
## [19405] 5 2 4 3 3 4 1 2 2 1 1 1 2 5 1 3 1 3 3 5 4 1 5 3 5 4 3 2 1 3 3 4 4 1 5 1
## [19441] 5 4 2 4 3 4 1 4 3 1 4 3 2 2 5 1 2 3 4 2 1 5 2 1 5 2 1 4 1 2 1 1 4 3 5 3
## [19477] 1 1 3 3 4 4 4 4 4 5 4 4 4 1 4 5 5 2 5 3 3 4 5 2 2 2 3 1 5 2 5 5 2 1 3 1
## [19513] 4 2 5 2 2 2 4 1 4 5 2 5 1 2 1 4 4 3 5 2 3 3 1 2 2 2 3 3 5 3 2 1 1 5 5 4
## [19549] 3 5 2 2 2 2 2 2 4 4 1 4 4 5 2 5 1 5 4 1 1 3 4 2 3 1 5 2 4 3 5 3 2 5 3 2
## [19585] 2 3 5 5 1 3 1 3 5 2 2 3 2 2 1 2 3 5 5 5 2 2 4 5 4 4 4 4 4 2 4 2 4 3 1 4
## [19621] 2 1 1 3 1 1 4 2 1 1 3 5 3 1 5 5 5 4 4 2 4 1 5 5 3 5 1 2 4 1 5 5 3 2 2 5
## [19657] 2 4 1 3 1 5 5 4 2 5 1 2 1 5 2 1 2 4 5 1 1 3 3 5 2 4 1 1 2 5 4 1 3 2 5 2
## [19693] 4 5 3 1 1 4 2 3 5 3 1 4 3 5 2 5 4 4 2 1 3 1 5 2 2 1 5 1 4 2 2 3 2 1 4 2
## [19729] 4 3 1 4 5 2 2 2 2 5 5 5 5 5 1 5 1 4 2 1 3 1 2 5 4 3 1 1 2 2 3 2 2 4 2 1
## [19765] 5 4 5 4 3 5 1 4 4 2 4 2 5 2 5 5 2 5 3 4 5 3 2 1 4 2 4 3 5 2 4 3 5 4 2 3
## [19801] 3 2 4 5 4 1 2 3 4 4 3 1 3 1 1 2 5 1 1 3 4 3 4 5 5 5 5 3 3 5 5 3 1 3 2 4
## [19837] 5 1 4 1 3 3 1 3 3 1 4 3 5 5 3 3 2 5 3 1 1 4 1 1 1 5 5 4 5 2 2 2 5 4 5 2
## [19873] 3 5 4 2 3 1 3 2 4 1 5 4 3 5 2 4 2 3 3 2 5 5 1 5 3 4 3 1 3 1 2 2 1 5 4 3
## [19909] 5 1 5 5 3 1 4 4 5 5 2 2 4 2 4 5 4 1 2 3 4 1 4 1 3 2 5 2 2 5 5 1 5 4 2 3
## [19945] 3 5 4 4 3 1 3 3 1 5 1 5 2 2 3 5 2 4 5 4 3 3 2 3 2 5 4 4 5 1 3 3 5 2 1 5
## [19981] 2 5 3 4 1 2 4 3 5 3 2 5 1 2 2 2 5 5 2 4 2 2 1 1 2 1 5 1 3 4 1 2 2 4 5 2
## [20017] 2 1 3 2 2 4 3 4 5 4 3 2 3 5 5 5 5 5 1 1 2 4 5 1 3 5 1 3 4 2 4 4 3 4 4 2
## [20053] 3 5 3 4 1 5 3 3 2 1 5 5 5 5 3 4 3 4 3 3 2 2 3 3 1 1 5 2 5 2 4 2 5 1 4 4
## [20089] 2 5 1 1 5 5 5 5 1 4 2 5 3 5 3 3 2 2 3 5 3 5 1 3 2 3 1 4 2 2 2 4 3 2 4 5
## [20125] 1 3 2 5 3 5 2 5 2 3 5 3 1 2 5 5 2 1 3 2 3 4 1 2 3 4 3 3 1 4 3 2 2 1 2 3
## [20161] 2 2 5 3 5 2 4 3 4 3 3 4 1 2 3 4 3 2 3 5 5 2 4 5 1 3 4 3 4 3 5 1 4 2 4 3
## [20197] 4 1 5 5 1 4 2 1 1 4 4 3 4 3 3 4 5 4 5 4 5 5 3 3 2 3 3 3 3 4 1 2 5 3 2 2
## [20233] 4 2 4 4 2 1 3 2 4 3 4 4 2 3 4 4 3 2 3 4 4 5 5 2 5 4 3 2 4 2 3 4 5 2 5 5
## [20269] 4 3 2 2 1 2 4 3 4 2 5 4 2 3 4 5 5 2 5 5 5 3 1 1 3 4 5 4 3 4 2 5 5 4 1 4
## [20305] 2 1 5 4 1 3 4 1 1 1 2 5 4 2 3 5 1 3 2 5 3 3 1 5 1 1 1 2 2 5 1 3 3 2 3 2
## [20341] 2 4 1 5 5 5 1 5 2 4 1 3 3 4 3 4 2 2 4 4 4 1 4 1 5 4 1 2 4 2 2 2 4 1 5 3
## [20377] 1 2 2 4 1 3 5 4 3 3 1 3 2 5 3 1 1 3 1 3 3 5 5 1 1 3 3 4 5 5 3 5 2 2 2 3
## [20413] 3 3 2 1 1 2 4 5 3 1 3 5 3 4 3 1 5 2 3 3 1 2 1 1 4 4 3 3 3 1 3 5 2 5 1 3
## [20449] 3 4 1 1 5 3 3 1 5 1 1 2 1 2 2 5 1 2 1 2 4 2 2 3 1 2 1 2 2 1 5 1 1 2 1 1
## [20485] 1 3 2 3 2 2 5 4 4 5 2 5 1 1 2 3 3 1 3 4 2 4 2 3 5 3 4 2 5 1 4 4 4 5 4 2
## [20521] 4 2 2 1 3 1 1 5 5 5 4 2 2 1 5 4 4 1 5 5 5 4 3 3 5 5 4 5 2 5 2 4 2 1 5 5
## [20557] 3 3 5 4 5 2 2 2 5 4 5 1 4 3 1 2 4 2 1 5 3 5 1 3 2 5 2 4 5 3 5 3 1 3 1 3
## [20593] 3 4 5 3 3 5 3 1 3 2 5 1 5 1 5 5 4 1 1 3 5 4 2 5 2 2 1 3 5 4 3 3 3 1 2 5
## [20629] 2 1 3 4 4 5 4 4 2 3 4 5 5 1 1 4 2 1 1 2 2 1 5 1 5 4 5 2 5 1 5 2 5 3 5 3
## [20665] 1 1 4 1 3 5 4 5 4 2 1 2 2 3 3 4 1 3 3 4 3 2 3 4 3 1 3 4 4 2 5 3 2 2 1 2
## [20701] 2 5 4 1 4 3 5 5 4 5 4 4 1 3 3 5 4 1 1 5 2 3 2 1 4 1 4 1 2 4 3 3 1 3 2 4
## [20737] 3 4 4 5 3 2 1 4 4 5 3 3 5 5 4 3 1 4 1 5 5 2 1 2 1 5 3 2 1 1 4 5 1 3 2 3
## [20773] 2 1 1 4 1 1 1 2 4 3 3 1 1 1 3 1 3 5 5 4 4 1 5 4 5 3 2 3 3 2 5 1 2 5 2 2
## [20809] 1 2 1 5 5 2 1 4 5 5 4 5 4 4 5 2 5 1 1 3 3 5 5 1 5 2 4 5 1 5 3 4 5 5 2 3
## [20845] 1 2 1 3 2 1 5 5 3 1 3 3 1 4 4 4 3 5 3 1 4 2 4 4 2 5 3 3 2 4 3 3 5 5 1 4
## [20881] 4 4 2 3 3 1 2 4 3 3 2 4 1 4 3 3 5 2 1 1 4 5 2 1 2 3 1 3 3 2 2 3 4 2 5 2
## [20917] 1 3 1 4 1 2 3 2 4 3 4 1 2 3 5 1 4 5 4 3 1 5 2 2 1 2 3 3 1 3 5 3 1 4 3 2
## [20953] 5 1 3 1 1 4 1 2 4 4 4 2 5 4 2 2 3 1 1 1 1 1 4 3 3 4 4 5 4 5 4 2 2 5 1 4
## [20989] 3 3 1 1 3 5 2 5 5 3 3 5 3 3 1 2 2 3 4 2 1 4 2 3 1 1 3 3 4 4 1 5 5 5 5 2
## [21025] 1 5 5 4 2 5 3 2 4 4 4 5 3 1 4 5 1 4 3 4 2 5 3 1 2 4 3 5 1 2 3 1 2 3 1 2
## [21061] 1 5 2 1 4 1 4 3 3 2 5 4 3 1 4 3 2 2 1 3 2 4 5 4 2 3 5 3 2 4 3 2 2 5 4 4
## [21097] 4 4 2 4 2 1 4 4 2 5 1 5 4 2 5 2 2 5 4 3 1 3 5 5 4 2 4 3 4 1 4 1 1 3 3 5
## [21133] 1 5 5 5 5 3 1 3 1 1 3 1 2 2 5 5 5 2 5 4 4 4 2 1 2 3 1 4 5 1 1 1 1 2 2 2
## [21169] 3 4 1 4 2 2 5 4 2 5 2 4 2 5 5 5 1 1 4 2 4 2 4 1 5 4 1 5 2 5 2 3 4 2 2 2
## [21205] 1 5 1 2 2 4 1 4 5 2 3 1 1 3 4 3 5 2 4 5 2 3 1 4 4 1 1 2 4 3 5 1 1 4 5 2
## [21241] 3 2 4 1 5 4 4 5 5 4 2 1 5 5 5 1 5 1 2 1 2 4 5 2 2 2 5 3 4 5 1 2 2 1 3 1
## [21277] 2 4 3 4 5 3 2 1 5 4 2 1 1 4 2 4 2 4 3 3 4 4 4 1 4 2 5 5 2 4 4 3 5 3 5 5
## [21313] 3 5 2 5 3 4 1 4 3 2 1 3 5 5 1 1 3 4 1 5 5 3 1 1 2 1 5 5 3 5 4 5 5 3 5 1
## [21349] 3 4 3 2 1 2 5 5 1 5 1 4 1 1 2 3 3 1 5 4 1 1 1 2 3 1 4 4 5 2 3 4 4 1 3 4
## [21385] 2 4 1 2 5 1 4 5 5 4 1 5 1 3 5 4 4 2 2 2 4 3 1 4 1 1 2 3 1 4 2 1 1 2 4 2
## [21421] 3 4 5 3 3 3 5 3 1 4 2 5 4 2 5 2 1 5 4 3 4 3 4 3 2 2 2 3 4 5 2 3 4 2 4 3
## [21457] 5 3 2 2 1 3 4 5 3 4 4 5 3 1 2 4 1 3 1 5 5 2 2 5 1 1 5 2 1 5 4 5 4 2 1 1
## [21493] 2 2 3 1 1 2 4 4 4 3 5 1 3 5 3 1 1 3 2 4 2 2 1 1 2 5 4 5 4 1 3 5 1 1 5 5
## [21529] 2 5 4 3 2 5 5 3 3 1 5 4 1 1 3 2 2 5 4 1 3 3 2 2 3 2 5 5 3 3 4 2 5 3 5 2
## [21565] 5 5 3 1 5 5 3 1 3 1 4 3 5 1 4 1 2 1 2 5 1 4 3 4 4 1 3 5 1 1 4 1 3 2 3 3
## [21601] 3 3 3 2 2 4 5 2 1 1 5 4 5 3 5 3 5 3 4 3 4 5 4 2 5 1 4 3 3 3 1 1 4 1 3 3
## [21637] 2 3 1 2 2 4 4 1 1 3 3 4 5 5 5 3 1 4 1 4 3 4 2 4 3 2 4 4 2 3 5 4 1 3 2 3
## [21673] 1 4 2 3 2 5 3 2 4 4 3 4 3 1 4 1 1 5 1 1 5 4 2 1 1 1 2 2 5 2 5 4 1 1 3 2
## [21709] 2 5 2 3 1 5 2 1 1 3 2 2 3 1 2 2 4 2 2 5 3 3 2 1 5 5 1 3 1 5 1 1 3 5 5 4
## [21745] 2 4 5 2 2 4 3 1 2 3 3 3 5 5 5 2 1 4 5 1 3 5 3 4 3 2 1 1 4 1 3 1 4 3 3 4
## [21781] 2 5 3 1 5 5 1 2 5 3 2 3 1 4 3 3 1 5 4 3 4 4 1 3 4 5 3 1 3 2 2 1 5 4 3 2
## [21817] 5 3 1 1 1 3 1 4 1 2 3 5 2 2 1 2 4 3 4 3 2 2 4 5 3 1 1 2 3 2 1 4 3 1 1 5
## [21853] 3 5 3 2 5 1 4 2 4 1 4 3 3 3 3 2 5 5 2 3 5 3 5 5 2 1 5 5 3 4 2 4 3 4 1 4
## [21889] 1 1 5 4 4 4 3 1 2 1 3 2 1 1 2 2 2 3 1 3 3 4 4 4 1 1 2 4 1 2 5 1 3 2 5 3
## [21925] 5 1 2 3 2 4 2 1 2 1 2 3 3 5 4 5 5 1 1 4 1 4 1 4 3 2 2 5 5 3 4 3 5 5 1 1
## [21961] 3 3 1 3 3 4 4 2 1 2 1 4 5 2 4 2 4 5 4 2 4 4 2 2 4 2 2 5 1 5 3 5 2 1 1 1
## [21997] 2 1 1 5 2 4 4 2 2 2 3 1 5 3 4 3 3 3 4 2 1 3 1 5 4 4 4 4 2 1 4 5 2 4 4 4
## [22033] 3 2 5 3 3 2 4 3 3 1 5 5 2 3 2 2 3 4 1 2 4 5 3 2 1 3 5 4 5 1 4 1 2 3 1 3
## [22069] 3 3 4 3 2 4 2 3 1 3 5 2 1 2 5 2 1 3 1 3 4 3 5 1 1 2 1 4 3 4 4 4 5 1 5 5
## [22105] 3 3 5 2 4 4 5 5 4 2 5 2 2 4 3 3 1 2 5 1 5 4 5 5 1 1 1 4 4 5 4 3 4 2 5 5
## [22141] 3 1 5 2 5 2 4 3 2 1 1 2 2 1 3 1 4 5 5 3 2 3 5 4 1 3 3 1 3 5 4 3 2 5 4 1
## [22177] 4 3 2 5 5 4 5 1 4 4 5 4 3 5 1 4 1 1 4 4 4 1 5 5 5 5 5 4 4 1 5 4 4 5 4 2
## [22213] 3 4 1 1 1 4 2 4 2 1 5 1 2 2 1 2 2 3 5 4 3 2 2 4 4 4 2 5 5 4 2 1 4 2 4 3
## [22249] 5 1 4 3 5 3 3 5 1 5 4 5 4 2 2 2 3 1 4 3 1 2 5 3 1 2 3 3 4 5 1 4 2 5 4 4
## [22285] 4 2 4 2 1 5 5 1 2 5 2 5 4 5 3 5 1 4 1 5 4 2 3 2 4 4 2 3 4 5 2 5 3 5 4 4
## [22321] 4 4 5 5 5 3 1 2 4 5 1 1 5 1 2 1 3 4 2 3 2 2 4 4 3 1 2 3 1 3 4 5 3 4 1 5
## [22357] 3 2 3 1 2 3 1 3 5 2 4 1 2 3 5 1 4 2 5 5 2 4 1 1 1 3 1 3 5 1 1 4 1 1 5 2
## [22393] 1 1 3 2 5 2 1 3 4 1 3 5 4 4 4 5 5 5 4 4 4 5 1 5 2 1 1 1 2 2 3 3 4 5 5 5
## [22429] 2 5 1 1 4 2 2 5 5 2 2 5 4 3 3 4 1 4 3 2 2 2 3 3 1 4 3 4 2 3 5 2 1 4 1 4
## [22465] 4 4 1 1 4 4 1 2 3 2 4 4 3 5 3 4 1 5 2 2 5 5 5 2 2 1 4 3 4 5 3 3 3 5 1 3
## [22501] 1 4 4 2 2 2 4 3 1 5 4 5 1 2 2 3 5 5 1 1 1 5 5 2 4 3 2 5 3 4 1 3 3 5 3 5
## [22537] 5 4 3 1 3 2 4 3 4 3 3 4 2 2 5 3 1 5 4 4 3 4 1 3 3 2 3 3 2 1 3 1 5 4 4 3
## [22573] 5 2 5 2 1 1 2 4 1 5 2 1 1 5 5 5 5 5 1 3 2 1 3 3 4 1 2 1 1 4 4 1 5 4 2 1
## [22609] 1 2 4 3 2 2 4 2 1 5 3 4 4 1 4 3 5 1 2 3 4 4 1 2 3 3 5 5 4 4 2 3 1 3 5 4
## [22645] 1 3 1 1 5 3 1 2 3 2 5 4 5 5 5 4 2 3 3 2 2 3 1 5 3 4 3 3 4 1 4 1 5 5 4 1
## [22681] 2 5 5 3 3 5 5 2 1 2 4 2 5 2 4 1 1 1 1 3 4 5 1 4 2 5 2 1 1 5 3 4 1 4 5 1
## [22717] 3 2 5 3 2 3 2 4 5 1 4 2 4 3 1 1 4 4 1 3 1 4 1 3 1 3 3 3 2 3 2 4 3 5 4 4
## [22753] 4 5 1 3 1 1 2 3 3 3 4 3 2 2 3 2 5 2 1 2 3 1 5 3 3 5 3 1 4 1 5 4 4 1 3 1
## [22789] 4 2 2 1 5 1 5 1 4 2 2 5 3 2 2 5 3 1 5 2 1 2 3 2 4 3 3 5 4 1 5 2 1 2 3 4
## [22825] 2 2 2 2 5 5 4 2 2 2 5 3 2 5 1 3 3 4 5 3 1 3 3 5 4 3 5 3 2 2 5 2 5 5 1 1
## [22861] 3 2 1 3 3 5 4 1 4 1 5 1 4 4 3 3 4 3 5 5 3 2 4 5 5 3 1 3 1 1 5 4 3 4 3 1
## [22897] 3 2 4 4 5 4 4 1 3 4 2 2 4 4 1 1 4 4 3 5 3 1 3 1 3 4 2 2 1 4 4 3 5 4 1 3
## [22933] 5 2 4 4 3 2 2 1 4 2 2 5 1 3 2 1 5 4 4 3 5 3 2 1 2 2 4 2 2 5 2 4 4 4 5 4
## [22969] 4 3 2 4 1 5 5 3 5 3 5 3 2 4 1 4 1 2 3 4 1 2 1 5 2 2 4 2 1 1 2 3 3 2 5 2
## [23005] 5 3 4 2 5 1 5 1 5 3 3 3 5 2 4 3 4 3 3 2 3 5 3 1 4 1 1 2 5 4 1 4 5 2 5 4
## [23041] 5 1 1 4 3 1 3 3 3 4 2 2 5 2 1 1 4 3 3 4 3 4 1 4 1 4 2 4 4 2 4 1 2 3 2 1
## [23077] 4 2 4 2 5 5 2 3 4 2 2 4 2 5 3 3 2 4 5 3 3 5 4 5 2 1 4 1 2 4 1 2 2 1 4 3
## [23113] 5 4 3 3 3 1 2 2 1 1 2 1 1 1 5 5 1 4 3 3 3 2 5 4 3 5 5 4 2 3 5 2 3 4 4 5
## [23149] 3 3 1 2 5 3 2 2 3 5 2 5 5 3 2 1 5 5 5 5 4 4 2 4 3 2 5 3 4 5 2 2 1 5 1 3
## [23185] 5 5 4 5 4 1 5 1 4 4 2 5 5 5 3 3 4 1 3 2 4 5 2 4 3 4 4 4 4 3 4 2 5 1 3 5
## [23221] 5 3 4 4 4 4 2 1 2 3 5 2 5 4 2 5 1 5 2 5 4 1 3 3 1 3 4 2 2 1 5 4 4 5 2 3
## [23257] 5 1 1 2 5 2 3 1 3 2 1 1 4 2 5 4 1 4 2 2 1 1 3 4 1 3 1 3 2 2 2 4 1 2 1 3
## [23293] 5 4 4 5 1 1 1 2 4 4 5 4 2 3 3 5 1 2 1 3 4 4 2 3 2 1 2 2 4 5 4 5 4 5 1 1
## [23329] 2 4 5 5 1 3 4 2 5 5 1 5 4 4 3 4 4 4 2 5 3 2 2 1 3 3 4 5 4 1 3 2 4 3 2 5
## [23365] 5 2 1 3 1 1 1 3 3 2 4 1 2 1 1 3 3 4 1 5 5 4 5 1 4 5 1 5 2 1 3 3 1 4 3 4
## [23401] 2 4 4 5 5 3 3 4 4 3 3 1 1 3 2 4 3 4 3 1 2 3 2 4 3 4 5 3 5 3 5 5 2 2 4 3
## [23437] 4 4 4 2 5 3 4 3 1 5 5 2 3 3 3 1 5 2 5 1 3 1 4 1 2 3 1 5 4 1 1 3 3 4 5 1
## [23473] 3 2 5 4 2 1 3 4 4 5 4 1 2 3 4 5 2 2 2 5 2 1 5 3 2 4 1 2 5 3 4 3 4 4 5 5
## [23509] 5 3 5 2 4 3 1 4 4 3 3 2 3 5 3 1 1 1 1 4 5 3 5 2 4 3 3 3 2 5 1 1 5 3 1 3
## [23545] 1 1 5 3 1 1 4 2 2 3 4 3 5 4 2 2 1 4 3 5 2 3 4 4 4 3 3 1 1 3 1 4 4 5 3 1
## [23581] 3 5 5 1 1 2 3 4 1 1 4 5 1 3 1 3 2 1 4 4 5 5 2 3 1 5 4 2 3 1 3 2 4 2 3 4
## [23617] 2 4 5 3 5 5 2 4 2 1 4 5 5 1 2 3 3 2 2 5 2 1 4 3 4 2 4 4 1 1 2 4 2 2 3 5
## [23653] 5 3 2 3 4 1 3 3 3 2 1 2 4 4 1 5 1 3 3 3 4 1 3 2 5 1 4 1 4 4 3 2 1 4 3 4
## [23689] 5 1 2 5 2 3 4 3 5 5 1 2 2 4 2 4 2 2 1 3 4 1 1 5 5 1 1 3 5 1 2 3 5 5 1 4
## [23725] 5 3 3 2 4 3 3 1 1 5 1 4 1 4 3 1 3 3 5 3 4 2 2 5 2 4 4 2 5 2 5 4 4 5 4 1
## [23761] 4 1 4 5 1 4 5 1 2 1 3 1 3 5 1 5 5 1 2 2 1 1 4 5 5 2 1 4 4 1 5 3 3 4 1 1
## [23797] 3 2 5 1 4 5 4 1 3 2 3 1 1 1 4 3 1 4 3 1 1 3 1 5 2 5 3 5 1 4 4 5 4 3 5 2
## [23833] 2 4 5 1 1 4 2 1 2 3 5 3 3 5 3 2 5 4 5 2 1 3 4 3 3 3 2 3 3 1 4 5 3 4 4 4
## [23869] 4 4 2 5 1 4 2 2 4 2 5 5 3 1 4 3 3 2 1 4 2 4 2 5 3 3 2 2 4 3 5 1 2 2 5 2
## [23905] 4 1 4 3 2 2 5 2 1 5 1 1 5 3 5 4 5 4 4 1 4 2 4 2 3 1 1 5 4 4 1 2 4 4 1 5
## [23941] 2 2 3 5 4 2 3 5 4 4 4 1 4 4 4 5 2 3 4 5 2 1 5 3 3 4 4 3 3 1 2 2 2 3 1 1
## [23977] 3 3 5 2 1 1 5 5 1 2 3 5 4 3 3 4 3 4 4 5 4 5 2 2 2 4 4 4 2 2 2 2 5 3 2 1
## [24013] 1 3 1 1 3 5 5 2 1 1 2 4 3 5 4 2 2 1 1 5 3 1 5 5 1 2 2 3 3 3 1 2 5 3 4 1
## [24049] 3 4 5 3 5 4 2 2 4 3 5 5 2 2 1 5 2 5 4 4 1 5 1 2 2 2 1 2 4 3 3 4 4 2 3 5
## [24085] 2 4 5 3 4 2 4 5 4 2 3 5 3 2 4 4 1 1 1 4 5 5 2 5 2 4 3 2 5 1 5 3 1 2 3 3
## [24121] 1 3 2 2 1 5 3 4 5 2 1 5 5 3 1 2 3 3 1 4 2 2 1 3 5 3 5 4 4 2 4 5 5 1 1 5
## [24157] 1 5 1 5 1 4 2 2 3 1 1 5 5 5 3 3 1 2 2 3 4 3 4 3 2 1 2 4 4 2 2 2 1 4 2 2
## [24193] 3 5 2 2 1 2 1 5 5 3 2 2 5 1 4 3 5 4 1 5 4 3 2 2 3 3 2 5 1 3 5 5 1 1 5 1
## [24229] 3 1 2 3 4 1 5 2 3 1 1 5 3 1 5 2 3 1 5 3 4 4 5 1 4 5 3 3 5 1 5 1 5 5 4 5
## [24265] 4 3 3 3 1 2 2 5 5 5 1 4 5 2 4 2 3 3 5 2 3 1 2 4 3 4 2 5 5 4 4 5 5 4 1 3
## [24301] 3 1 3 4 4 3 4 3 4 5 4 4 5 1 1 2 2 1 4 5 1 1 3 5 1 4 1 1 1 2 2 2 1 2 2 5
## [24337] 5 4 4 1 1 5 3 4 3 2 1 1 1 2 3 5 1 1 1 1 1 5 5 2 3 3 2 1 1 3 1 4 5 5 4 4
## [24373] 5 1 4 2 3 1 5 2 4 5 3 2 5 2 3 4 3 1 2 4 4 1 4 2 3 4 2 3 1 3 4 4 1 2 5 4
## [24409] 1 2 1 2 4 2 3 1 3 5 1 4 2 2 1 3 3 1 2 3 4 3 4 4 2 4 3 4 5 2 5 5 4 2 5 1
## [24445] 1 1 3 3 1 3 2 4 2 2 5 5 2 2 2 5 1 5 3 5 3 5 2 4 2 1 1 5 2 3 3 2 3 2 4 2
## [24481] 1 5 1 5 3 3 1 2 1 3 4 1 4 4 3 3 2 5 5 3 5 4 5 2 3 2 2 1 2 3 2 5 5 2 2 3
## [24517] 5 1 3 1 1 3 3 1 2 3 1 1 1 3 5 2 2 5 5 1 5 3 5 2 2 3 1 2 1 2 3 5 5 4 5 4
## [24553] 5 2 4 4 1 2 1 2 3 5 4 1 2 1 2 2 3 4 4 3 5 5 4 5 1 1 2 4 3 3 5 5 3 1 4 5
## [24589] 1 4 5 2 4 3 1 5 3 2 5 2 4 4 3 2 3 1 5 3 4 5 1 3 4 4 3 1 4 3 2 4 1 4 3 2
## [24625] 5 1 1 2 1 4 2 4 5 5 5 5 3 5 1 2 2 5 4 1 4 1 1 3 5 4 4 1 5 1 4 1 1 3 3 4
## [24661] 1 4 5 1 5 5 5 3 5 4 4 2 5 4 2 5 3 2 1 5 2 2 1 2 3 4 2 3 2 2 1 3 4 5 2 2
## [24697] 1 2 2 2 1 4 5 2 3 5 4 3 3 2 1 1 5 2 5 3 4 3 4 3 1 5 3 4 3 1 2 1 3 4 1 2
## [24733] 1 1 1 5 3 3 5 2 3 4 3 1 5 4 3 1 5 2 2 3 3 2 2 3 2 5 5 4 2 1 5 4 1 2 3 1
## [24769] 1 3 5 3 2 3 4 1 2 3 1 2 1 1 2 4 3 2 5 1 2 3 1 5 1 3 4 2 1 4 2 4 5 3 3 1
## [24805] 3 5 4 4 5 5 3 1 4 4 2 1 3 3 5 5 5 1 4 5 2 2 2 2 5 3 5 4 2 5 1 4 5 1 2 1
## [24841] 1 1 5 2 5 1 1 1 1 1 1 4 2 4 4 4 5 1 2 4 2 1 5 4 5 1 3 2 4 5 1 5 1 5 2 4
## [24877] 3 5 3 2 5 3 3 5 5 2 5 2 1 2 1 4 3 5 3 5 5 1 1 5 4 2 5 3 3 1 4 4 5 4 2 4
## [24913] 2 4 4 2 3 2 3 1 1 4 3 4 1 1 4 3 5 4 1 2 4 1 5 4 1 2 2 2 3 5 1 2 1 1 2 1
## [24949] 2 4 2 1 1 3 2 5 1 1 4 2 5 4 1 3 3 1 4 1 1 5 3 5 5 4 2 5 2 4 1 5 5 3 5 3
## [24985] 3 2 2 5 5 4 2 3 2 5 1 4 2 1 4 1 2 1 2 1 2 3 2 2 3 3 4 2 4 5 2 1 3 5 2 1
## [25021] 3 3 2 4 5 4 5 1 4 5 3 5 1 5 1 5 3 3 2 2 3 1 3 4 3 5 4 4 2 4 5 2 4 3 5 1
## [25057] 1 5 4 1 5 1 4 2 5 4 3 5 5 2 5 1 4 4 5 4 2 1 4 3 1 2 5 1 4 4 3 4 3 1 2 4
## [25093] 3 4 5 4 5 4 1 5 5 4 3 4 1 5 3 1 5 3 3 5 1 5 4 2 2 5 1 4 4 2 4 2 2 2 1 5
## [25129] 2 2 5 1 5 1 3 1 1 5 4 2 5 4 4 3 4 5 4 3 1 1 3 3 5 5 1 5 4 3 4 3 1 3 4 3
## [25165] 3 2 3 3 3 1 1 4 5 3 1 1 5 2 4 3 1 2 3 1 2 3 5 5 2 4 2 5 4 2 1 3 1 5 3 4
## [25201] 4 2 5 3 2 2 4 3 4 3 3 3 3 1 1 2 2 2 2 2 1 5 4 5 1 2 3 5 2 1 4 1 1 3 4 4
## [25237] 5 1 5 2 2 3 5 1 3 1 4 5 5 5 2 2 3 3 4 1 4 2 2 2 5 2 4 4 2 4 2 4 3 5 4 1
## [25273] 5 5 4 4 3 5 5 4 3 5 5 2 4 4 5 4 1 1 4 2 5 4 2 3 2 5 4 3 1 2 3 2 1 2 5 2
## [25309] 5 3 1 1 5 1 4 1 4 3 1 1 1 2 5 5 3 5 4 2 5 3 4 2 4 3 2 4 5 3 5 1 1 5 3 3
## [25345] 4 2 4 5 1 3 1 2 4 1 4 1 2 5 2 4 4 1 5 2 2 2 3 4 5 4 4 5 4 2 1 5 3 3 3 1
## [25381] 2 4 2 1 4 4 2 3 4 1 1 1 3 1 2 1 4 5 1 3 2 3 2 2 4 3 4 2 4 2 3 5 5 3 1 1
## [25417] 5 4 2 4 2 4 3 1 4 5 1 5 4 2 5 4 4 2 1 1 4 5 3 5 5 3 2 5 2 3 5 5 3 3 2 2
## [25453] 2 4 2 5 4 5 2 3 5 4 2 4 5 4 1 4 5 5 3 3 4 3 3 5 5 5 5 3 3 1 2 3 3 1 5 1
## [25489] 5 2 1 3 5 5 2 1 5 4 1 4 3 1 4 1 1 5 4 2 4 4 2 2 4 2 5 3 2 3 1 4 3 4 5 1
## [25525] 1 3 5 4 1 2 2 4 1 2 1 1 1 3 5 3 3 3 4 4 1 3 2 4 3 4 2 3 2 4 1 4 5 3 4 2
## [25561] 3 4 2 2 2 4 5 1 4 1 5 1 5 5 4 5 2 4 3 1 3 1 3 1 2 4 5 3 1 4 5 1 4 1 1 2
## [25597] 1 4 5 1 5 1 3 5 3 2 3 2 4 3 5 4 4 1 2 2 3 2 4 3 5 3 3 3 5 5 3 4 4 3 3 4
## [25633] 2 4 3 1 1 3 5 3 1 1 4 3 4 1 5 1 5 2 4 2 4 4 4 2 1 5 5 3 5 2 1 3 3 4 2 1
## [25669] 3 1 1 1 4 2 2 3 4 5 1 2 3 2 1 4 4 2 3 2 1 3 4 2 1 4 1 2 4 4 4 4 2 5 1 1
## [25705] 3 1 4 2 5 1 5 5 4 4 2 1 4 2 2 2 5 2 4 5 2 3 4 1 3 5 4 5 3 3 2 2 4 4 3 5
## [25741] 2 3 1 1 1 5 2 3 5 2 3 2 4 2 2 4 4 3 3 1 1 2 4 2 5 5 4 4 1 2 5 2 2 5 1 2
## [25777] 3 5 2 1 3 3 3 4 4 2 5 2 5 2 5 5 1 4 1 2 4 5 1 5 2 4 3 3 1 3 4 4 4 3 1 2
## [25813] 2 3 3 4 1 5 3 4 4 2 4 4 3 3 2 1 3 3 1 5 3 3 1 3 4 5 4 1 5 2 1 1 2 4 1 4
## [25849] 4 2 5 1 5 3 4 5 1 1 2 2 1 3 1 2 4 5 3 1 4 5 3 2 4 4 2 4 1 2 1 2 2 5 4 1
## [25885] 1 5 1 4 2 2 5 1 2 5 3 3 5 5 5 2 4 5 3 5 4 1 5 4 1 3 2 4 1 1 3 2 4 4 3 1
## [25921] 3 3 5 3 4 5 2 1 3 4 1 3 3 1 1 1 3 4 5 3 4 2 4 3 4 3 3 4 5 5 5 3 3 5 2 3
## [25957] 5 1 3 5 1 3 5 4 2 1 4 2 1 5 3 1 3 2 4 2 1 2 1 2 1 4 3 5 1 3 2 5 1 3 1 4
## [25993] 4 4 3 5 2 4 2 4 2 2 1 3 5 1 3 5 3 5 2 4 2 4 5 1 5 2 1 1 3 3 2 1 5 4 4 2
## [26029] 4 3 4 2 1 1 2 3 5 1 3 3 3 5 2 2 1 4 4 3 3 4 4 2 3 4 1 5 2 4 2 4 2 3 1 5
## [26065] 5 3 1 5 3 2 5 5 3 1 1 4 3 1 1 1 5 5 1 4 3 4 2 4 2 2 5 2 1 3 1 3 3 1 4 2
## [26101] 1 4 1 5 2 5 2 1 2 1 5 5 5 5 5 1 3 1 4 2 3 1 4 4 5 3 3 2 2 2 4 2 1 4 3 3
## [26137] 2 5 5 2 3 1 2 4 3 2 4 5 5 2 1 5 4 4 1 5 4 4 1 5 4 3 5 5 3 1 4 2 5 3 4 4
## [26173] 4 3 1 5 2 4 1 1 1 3 5 5 5 2 3 2 3 4 2 1 4 5 4 4 5 4 1 5 4 3 3 2 4 1 4 4
## [26209] 1 3 2 2 1 5 5 4 4 4 3 4 4 5 4 5 4 1 1 3 5 5 3 3 3 5 3 3 2 5 3 5 2 1 4 1
## [26245] 1 3 2 2 3 4 3 4 4 3 2 2 1 1 1 2 3 2 1 5 5 5 1 4 2 2 2 1 1 2 4 5 4 2 1 4
## [26281] 1 2 2 3 1 2 2 2 3 3 4 4 2 1 4 1 1 4 2 3 5 4 4 3 2 1 3 3 1 4 4 2 3 4 4 3
## [26317] 1 5 5 5 2 1 2 1 5 2 1 1 2 2 5 2 2 1 3 5 4 1 4 1 1 1 4 3 5 3 4 2 2 4 3 3
## [26353] 2 4 5 2 1 1 4 2 4 3 3 1 3 1 4 4 4 5 4 1 4 2 5 4 2 4 1 5 3 2 4 1 4 4 2 1
## [26389] 4 1 2 3 5 5 1 3 4 3 2 4 4 2 3 2 2 2 3 3 3 5 3 1 3 2 1 1 4 4 4 3 5 5 1 5
## [26425] 4 2 2 4 3 1 3 1 1 2 5 1 3 2 1 4 1 1 3 3 4 5 3 4 2 5 1 1 4 1 1 1 1 1 3 5
## [26461] 5 5 4 3 4 2 2 4 1 3 5 4 5 5 2 2 3 5 4 3 4 3 4 1 5 5 2 5 4 4 3 4 2 1 2 5
## [26497] 1 4 3 3 2 2 2 1 5 4 4 4 5 5 5 5 4 5 3 1 5 5 2 4 2 1 1 5 3 3 1 5 3 2 2 3
## [26533] 2 5 2 1 3 4 4 3 3 5 5 5 3 1 2 3 5 5 1 1 2 5 1 4 4 1 3 5 4 3 2 3 5 1 4 1
## [26569] 1 5 2 2 3 4 5 4 1 3 5 3 4 3 3 1 4 3 3 4 4 1 2 4 3 1 3 4 1 3 2 1 1 5 4 5
## [26605] 2 4 3 5 1 5 1 4 5 1 5 4 4 4 2 5 1 1 2 2 3 1 2 2 5 2 2 1 3 3 4 4 4 5 2 3
## [26641] 2 5 3 1 3 5 4 5 4 5 4 2 5 1 5 5 2 3 3 4 1 5 5 3 3 3 1 3 5 3 3 4 2 2 4 5
## [26677] 5 2 4 2 4 3 2 3 3 4 1 5 2 1 3 5 3 5 1 1 2 5 5 1 5 4 3 4 2 1 3 2 1 1 1 3
## [26713] 1 5 1 3 3 4 1 4 2 5 5 5 5 4 4 5 1 2 1 4 5 3 3 4 5 2 5 4 1 4 1 4 1 3 1 5
## [26749] 2 4 4 2 5 4 1 3 2 4 1 2 1 3 2 5 2 4 3 3 4 4 4 4 3 4 1 3 2 2 3 2 4 2 5 4
## [26785] 5 4 1 5 5 3 5 3 1 2 3 4 3 5 5 3 5 1 5 1 3 1 1 2 5 2 2 4 3 5 1 1 4 2 5 5
## [26821] 3 5 4 5 4 2 2 5 3 4 4 5 3 3 1 1 4 5 1 1 2 2 2 1 2 3 5 4 5 5 2 5 3 4 1 1
## [26857] 2 2 4 3 3 1 2 2 4 1 1 4 1 5 1 5 5 2 1 3 3 5 1 1 4 5 1 1 2 4 5 4 4 1 5 1
## [26893] 3 1 5 3 5 3 4 5 5 5 4 3 1 3 2 5 2 3 4 5 5 4 2 1 1 3 5 1 5 3 2 5 4 5 3 2
## [26929] 3 5 5 1 4 4 4 2 5 1 2 4 3 3 5 4 2 5 1 5 5 4 5 4 4 1 2 3 1 1 4 4 1 2 4 2
## [26965] 1 5 3 2 2 4 2 5 3 1 2 4 5 3 4 4 4 3 5 1 2 1 3 4 3 1 5 1 3 3 3 2 5 1 5 2
## [27001] 3 4 4 2 2 1 1 3 4 1 3 5 4 3 2 3 4 3 4 3 5 5 5 3 2 2 5 2 4 2 2 4 4 1 5 1
## [27037] 4 1 5 1 3 4 3 5 5 3 2 3 3 5 2 2 2 1 3 1 2 3 3 3 2 4 1 1 5 3 3 3 2 3 1 2
## [27073] 3 3 1 5 4 4 2 2 3 1 2 5 4 5 1 3 3 1 5 3 5 1 1 1 2 5 3 2 1 5 2 3 3 1 1 4
## [27109] 1 5 2 2 1 2 5 5 3 5 2 4 1 1 5 2 2 2 1 2 5 4 1 3 5 2 2 3 5 3 4 1 1 3 1 3
## [27145] 2 3 1 4 1 2 3 5 1 3 3 3 2 2 4 3 5 3 1 2 4 2 3 5 2 3 4 1 4 1 5 3 5 4 4 5
## [27181] 3 2 1 5 3 3 1 2 1 1 4 1 5 3 1 4 4 3 3 2 2 4 5 5 1 1 5 5 2 3 3 4 4 5 1 2
## [27217] 5 1 5 1 2 5 5 2 1 3 3 1 5 4 5 1 4 3 2 5 5 3 5 2 2 3 2 1 4 2 2 2 5 5 4 3
## [27253] 3 3 5 1 1 3 1 5 4 5 5 4 1 4 3 2 4 5 4 2 3 1 5 3 4 2 3 3 1 4 4 1 3 4 5 3
## [27289] 1 4 2 2 3 3 4 4 5 5 4 5 3 1 4 5 5 1 3 3 1 2 5 4 4 5 2 5 1 2 5 2 2 3 5 4
## [27325] 3 2 5 2 3 3 1 4 2 2 5 3 5 1 2 2 2 5 3 5 1 5 3 5 2 5 4 5 4 4 3 1 4 1 4 2
## [27361] 5 1 1 5 1 1 2 5 4 2 3 2 5 2 4 5 1 2 1 5 4 2 2 1 2 5 1 3 4 3 5 1 5 1 4 2
## [27397] 5 5 2 1 1 3 2 4 3 2 2 1 1 4 5 2 1 4 2 1 3 2 2 5 4 1 3 2 5 1 1 1 5 2 1 2
## [27433] 4 1 1 5 1 1 1 3 2 4 3 3 3 1 1 3 1 5 1 2 3 2 1 4 2 5 4 1 5 2 5 2 2 1 4 5
## [27469] 4 1 1 5 5 3 3 4 1 5 1 1 4 5 4 5 5 5 2 2 4 1 1 1 1 2 2 4 4 4 1 5 1 4 4 2
## [27505] 3 3 4 4 5 1 4 5 1 5 2 4 4 1 4 1 5 4 4 5 2 2 4 5 4 4 2 2 1 2 4 5 4 4 2 1
## [27541] 4 5 3 5 4 1 5 2 1 5 3 3 1 4 3 2 2 2 2 2 3 4 3 3 3 1 2 1 3 3 4 2 2 3 4 4
## [27577] 4 2 4 2 4 1 2 4 1 5 5 4 5 4 3 1 1 4 1 3 1 5 1 2 4 4 2 5 1 4 5 5 4 3 5 5
## [27613] 1 1 2 5 2 2 5 3 3 4 2 3 5 1 1 5 2 5 4 4 5 1 2 4 2 1 5 2 2 1 3 4 2 5 2 2
## [27649] 5 5 1 1 1 1 1 1 2 1 3 5 4 1 4 1 3 5 4 3 5 2 3 4 3 3 1 4 3 2 2 1 4 2 2 2
## [27685] 2 3 2 5 3 1 1 3 2 4 5 3 1 3 1 4 3 3 2 4 4 5 4 2 4 5 4 2 4 1 5 3 3 4 4 4
## [27721] 5 1 3 1 1 4 4 5 3 1 1 5 1 4 2 4 4 2 5 4 3 2 5 3 3 2 2 4 5 1 5 2 3 3 4 1
## [27757] 3 2 1 1 3 3 5 5 2 1 3 5 3 4 4 3 4 5 5 4 4 5 4 4 1 3 2 4 4 5 4 3 1 2 4 4
## [27793] 5 4 5 5 2 2 5 3 5 1 5 3 3 1 5 3 1 2 5 3 5 3 5 4 1 3 5 2 1 3 1 2 5 3 1 5
## [27829] 5 1 1 1 4 4 1 5 1 3 3 2 2 5 4 1 3 4 1 1 2 4 2 1 4 1 1 3 5 1 1 2 4 4 5 4
## [27865] 4 2 3 3 2 1 1 5 1 1 1 1 4 2 4 2 1 4 4 5 2 4 2 3 5 5 3 1 1 5 5 4 3 1 3 5
## [27901] 4 5 5 5 2 4 2 1 3 5 2 3 1 1 5 1 5 2 3 2 2 3 3 4 3 1 5 5 5 1 1 1 5 3 3 1
## [27937] 2 4 3 1 5 3 5 1 4 5 4 1 4 1 2 4 2 2 2 3 1 4 1 5 1 4 5 1 3 4 1 5 4 1 1 4
## [27973] 1 3 3 4 4 5 2 1 1 3 3 5 5 2 3 2 1 4 1 3 4 2 1 1 2 5 1 5 2 5 2 2 1 4 1 5
## [28009] 5 5 5 4 5 1 3 2 3 1 3 3 1 4 2 5 2 3 3 1 1 3 4 1 4 1 4 4 5 2 2 2 5 3 3 5
## [28045] 2 5 2 3 3 5 5 1 1 3 5 5 1 5 5 2 4 4 3 1 2 2 5 2 3 2 2 5 2 2 3 3 4 4 3 4
## [28081] 3 3 2 3 2 5 4 4 4 4 2 1 5 4 5 4 3 4 2 5 4 2 5 3 5 4 4 2 4 3 1 3 4 4 3 5
## [28117] 1 5 3 1 4 2 5 4 4 3 5 4 2 5 5 1 3 2 1 5 2 3 2 1 5 3 3 4 4 2 5 4 2 4 3 4
## [28153] 2 2 2 1 5 2 5 3 2 4 4 2 4 1 2 3 2 4 1 4 1 4 2 5 2 5 5 5 3 3 1 4 3 5 3 5
## [28189] 1 2 2 2 2 5 2 3 4 5 3 4 3 5 1 1 5 3 4 4 4 1 5 1 3 5 5 4 2 2 3 1 2 4 2 1
## [28225] 5 3 2 4 2 3 1 2 4 5 1 1 3 5 3 3 4 4 3 5 2 2 4 1 3 2 5 3 3 4 3 4 4 1 5 5
## [28261] 4 4 2 1 5 1 2 3 2 1 5 5 3 4 4 1 2 2 4 4 4 2 2 5 1 5 2 5 3 2 5 1 2 1 3 5
## [28297] 2 3 4 3 2 3 4 2 4 2 3 3 2 5 1 3 1 5 3 3 1 1 4 1 5 3 5 4 1 5 3 4 3 1 1 2
## [28333] 4 1 4 4 5 3 2 1 5 2 4 2 2 1 3 2 2 4 4 2 3 1 3 2 1 3 5 3 3 3 4 4 5 2 4 2
## [28369] 3 5 5 3 5 5 3 5 1 4 3 5 1 4 2 4 1 3 2 3 3 4 2 4 5 4 4 3 1 3 2 3 1 1 5 4
## [28405] 1 1 2 3 1 4 2 5 3 5 4 5 4 5 3 4 4 5 5 2 3 5 1 2 3 5 1 2 4 5 4 1 2 1 4 3
## [28441] 1 4 1 4 4 2 3 1 1 1 4 3 2 2 4 3 5 3 1 3 1 1 1 1 3 5 3 5 1 5 5 5 1 2 2 3
## [28477] 3 3 4 4 1 3 1 4 3 3 4 5 1 2 2 4 5 5 2 1 3 4 3 1 2 5 4 2 4 3 1 3 3 3 3 3
## [28513] 5 5 1 1 3 2 1 1 3 3 4 3 2 2 3 4 1 2 1 5 2 1 1 3 4 2 2 2 4 4 5 3 5 3 3 5
## [28549] 5 4 3 3 4 1 5 3 1 5 1 5 2 5 4 1 3 2 2 1 3 1 1 5 3 5 2 3 5 3 1 1 5 5 5 3
## [28585] 5 2 1 1 5 4 3 5 5 3 4 4 4 4 1 1 2 3 4 5 5 3 2 4 5 2 5 4 3 1 4 1 1 5 1 5
## [28621] 2 3 3 1 2 3 4 1 4 2 4 2 2 1 2 5 1 3 3 2 1 4 1 5 1 1 5 5 2 3 5 4 4 4 1 3
## [28657] 4 5 5 1 4 3 4 1 1 1 2 4 5 1 1 4 3 4 1 2 1 3 2 3 3 5 1 3 1 3 3 1 3 2 4 1
## [28693] 3 3 1 4 1 3 1 1 1 5 2 1 1 3 3 5 4 5 4 3 4 4 2 1 5 3 4 5 3 1 4 5 1 2 3 5
## [28729] 5 3 2 5 5 3 3 3 2 5 3 1 4 3 2 2 2 2 1 4 5 5 4 4 4 3 3 4 4 4 2 2 4 1 2 4
## [28765] 4 1 4 2 1 1 2 2 1 3 1 3 2 3 2 4 1 1 1 3 1 1 1 2 2 3 3 3 2 1 1 3 5 2 1 1
## [28801] 4 4 3 2 2 2 1 2 5 5 1 5 5 1 4 4 2 4 3 3 5 4 2 4 2 5 4 4 5 1 3 2 5 4 3 2
## [28837] 3 3 3 2 1 3 5 1 3 4 5 3 4 2 2 1 4 5 1 4 5 5 3 1 2 4 3 1 4 1 3 5 3 2 1 1
## [28873] 3 3 3 4 5 3 3 3 2 5 1 1 1 2 4 3 4 3 5 2 3 2 4 2 4 2 1 4 5 4 4 2 4 5 5 1
## [28909] 5 2 5 3 4 4 3 5 2 2 2 2 1 2 5 3 5 4 3 4 5 3 3 5 5 3 5 5 4 4 5 4 5 2 3 5
## [28945] 5 5 3 3 3 2 1 3 2 5 2 4 3 2 4 2 1 4 4 1 3 1 5 4 3 4 1 1 3 1 2 2 1 3 2 4
## [28981] 5 1 1 4 4 2 4 4 5 1 4 4 1 3 5 1 3 2 5 3 3 4 1 5 2 5 3 4 5 4 4 1 2 4 3 5
## [29017] 3 2 3 2 4 2 4 4 1 5 3 4 5 5 4 5 2 3 1 3 2 4 2 2 3 4 1 3 5 1 2 1 3 4 1 2
## [29053] 2 2 1 2 4 1 2 3 1 4 3 3 4 3 1 2 5 4 2 2 5 4 5 3 1 2 1 5 1 5 4 2 4 2 2 1
## [29089] 1 5 3 1 3 2 3 2 2 2 1 3 3 4 4 2 1 5 5 3 2 1 3 5 1 5 3 4 4 5 1 3 4 2 4 3
## [29125] 1 4 1 1 2 4 2 2 3 4 5 3 1 1 2 1 4 1 2 2 5 2 5 4 2 1 3 5 5 4 4 3 5 2 2 4
## [29161] 1 1 3 5 2 3 3 1 2 5 2 4 3 3 4 3 1 3 1 4 5 4 5 1 5 2 5 4 4 4 3 4 3 2 3 5
## [29197] 4 1 2 5 1 2 5 2 3 4 4 4 4 4 5 1 4 5 3 3 4 5 5 4 3 3 2 3 4 5 1 3 3 3 2 3
## [29233] 5 5 2 1 5 2 5 4 5 3 2 5 5 5 4 2 1 1 3 1 4 2 2 5 1 5 3 5 5 5 2 1 4 4 5 3
## [29269] 1 5 2 2 1 2 4 3 1 4 5 1 2 5 5 3 5 5 3 5 5 1 5 1 4 5 2 5 5 5 1 5 3 5 3 4
## [29305] 2 2 1 5 5 5 1 3 4 5 3 3 2 1 1 3 2 4 1 1 4 5 5 5 2 4 4 5 1 4 4 5 1 4 3 1
## [29341] 1 5 5 1 5 3 4 2 5 1 4 1 5 2 3 5 4 4 3 3 5 3 5 1 2 5 5 1 4 2 2 3 2 2 2 5
## [29377] 1 2 3 1 3 3 3 1 4 4 5 2 1 1 3 1 4 5 1 2 2 2 1 3 4 3 2 5 3 5 1 1 2 1 5 5
## [29413] 4 3 3 1 4 2 1 3 2 1 2 3 4 5 1 3 1 3 2 3 2 4 2 4 3 1 1 2 2 4 4 4 4 2 4 4
## [29449] 2 2 5 4 3 5 2 2 1 5 2 3 3 5 1 5 5 4 1 5 1 1 3 5 4 2 2 4 1 5 4 3 5 2 3 4
## [29485] 4 1 1 4 4 4 1 5 4 2 5 5 1 4 3 3 5 2 2 5 1 5 5 3 3 5 4 2 1 5 1 5 3 4 4 5
## [29521] 4 5 1 4 4 4 2 1 1 4 1 5 5 1 2 1 5 1 5 2 1 5 2 2 3 3 2 5 3 4 3 4 4 2 4 2
## [29557] 1 5 1 4 5 1 1 3 5 2 2 2 3 4 3 4 2 4 3 1 1 2 4 4 2 2 3 1 2 3 2 3 2 1 4 5
## [29593] 3 5 5 2 4 3 4 3 1 2 3 4 3 3 5 1 2 2 2 5 1 4 1 1 2 3 3 2 1 3 5 4 1 1 2 4
## [29629] 5 2 3 2 3 3 5 3 1 3 5 4 5 4 4 3 1 2 1 4 1 2 5 5 3 5 1 4 4 3 2 2 2 1 3 1
## [29665] 4 1 2 4 1 5 2 2 1 5 2 1 5 5 2 3 4 4 3 1 4 5 4 4 5 1 1 4 2 4 1 4 4 5 5 3
## [29701] 3 3 4 3 2 5 5 4 2 4 1 3 2 4 2 3 1 2 4 3 1 4 4 2 1 1 1 2 1 3 3 4 4 2 4 5
## [29737] 5 2 3 1 1 1 2 1 4 1 5 3 2 1 3 1 2 5 4 5 3 3 5 3 3 1 4 3 4 2 5 2 1 1 5 4
## [29773] 1 1 3 2 1 3 4 5 2 2 1 5 2 5 2 2 4 3 4 4 5 1 4 1 3 5 3 2 4 1 4 1 4 2 4 4
## [29809] 2 1 5 5 3 4 3 2 4 3 5 2 3 2 1 2 1 2 2 1 1 4 5 2 2 2 3 5 4 2 3 4 5 3 4 1
## [29845] 4 3 4 3 2 4 5 4 4 4 2 3 1 2 2 3 4 3 5 5 5 1 3 5 5 1 2 2 5 3 4 2 3 1 5 4
## [29881] 5 3 4 5 1 2 4 5 5 1 4 2 4 1 5 4 1 3 4 4 5 2 3 3 1 1 4 1 3 4 5 4 1 4 2 5
## [29917] 2 4 1 1 4 5 3 3 5 2 2 1 2 2 3 2 3 5 2 3 3 5 3 1 5 5 5 5 1 2 4 5 5 2 1 1
## [29953] 4 1 2 3 4 2 4 1 5 4 3 4 1 3 1 3 1 2 2 3 4 2 3 2 3 1 1 3 4 1 1 3 4 3 2 5
## [29989] 3 5 4 2 1 5 1 2 5 2 4 4 3 4 4 4 4 2 3 1 5 1 3 4 4 2 5 4 2 4 2 1 4 4 5 5
## [30025] 2 1 3 5 2 4 1 1 5 3 1 5 1 5 3 1 5 3 1 2 4 5 2 5 5 5 3 2 5 1 4 2 5 3 4 4
## [30061] 5 1 2 4 4 2 2 3 1 3 4 5 2 5 1 4 3 2 1 1 4 3 4 2 1 5 1 5 2 2 2 2 4 2 4 4
## [30097] 4 3 5 3 3 4 4 1 2 2 5 5 3 1 2 3 4 1 4 2 2 5 2 1 4 2 3 2 2 2 3 3 5 3 4 1
## [30133] 4 5 2 3 4 5 3 2 2 5 2 4 4 4 4 5 3 4 1 1 2 5 4 5 5 1 3 4 4 1 3 5 1 4 3 3
## [30169] 3 4 1 4 2 4 1 1 3 1 3 2 4 3 3 1 1 3 3 2 5 3 2 4 3 1 3 2 4 1 1 4 3 4 3 1
## [30205] 2 5 5 2 5 3 4 5 4 4 5 4 3 2 5 4 5 5 2 3 1 5 4 4 1 4 2 4 3 3 4 1 3 4 5 3
## [30241] 1 1 1 1 3 1 2 3 3 2 2 3 4 2 1 5 2 3 2 3 1 2 3 1 1 2 5 5 3 1 4 2 2 5 4 4
## [30277] 1 3 3 4 1 5 4 3 3 1 3 4 1 5 4 2 5 2 2 4 3 2 2 3 5 1 2 5 4 2 1 1 4 2 2 4
## [30313] 4 2 5 3 4 2 1 1 3 5 5 5 1 2 3 5 5 1 5 3 5 3 1 5 4 1 5 1 4 3 1 5 1 3 2 3
## [30349] 1 2 4 5 1 4 3 4 4 4 2 5 4 2 1 1 2 1 3 4 1 4 4 3 1 4 1 4 5 2 3 4 4 1 1 5
## [30385] 2 3 5 3 5 3 4 2 4 3 3 4 4 4 4 2 3 1 2 4 4 1 2 5 4 1 3 4 4 3 5 3 4 1 2 5
## [30421] 5 5 3 5 2 5 4 5 1 1 5 4 3 3 2 4 1 1 5 2 3 4 3 1 4 5 3 5 2 4 4 5 5 5 4 3
## [30457] 3 3 4 2 4 3 2 1 3 5 1 5 1 1 4 2 3 5 2 3 5 3 1 2 2 4 5 5 1 4 4 5 3 3 3 2
## [30493] 5 4 4 2 3 5 1 3 3 1 5 3 3 5 2 4 5 3 5 4 1 3 2 4 5 1 3 4 1 5 1 5 1 1 5 1
## [30529] 2 4 4 1 1 5 5 2 1 5 1 2 3 3 4 3 5 5 2 1 2 5 3 4 5 5 4 5 3 4 3 5 5 5 5 1
## [30565] 5 1 1 1 4 2 4 5 4 4 4 1 4 5 3 4 5 4 5 3 3 4 2 5 2 2 3 1 1 2 1 2 2 4 3 1
## [30601] 4 2 5 2 2 2 3 1 4 1 5 5 4 5 3 2 3 4 4 5 5 5 3 4 3 4 2 1 1 1 3 2 3 5 1 3
## [30637] 4 5 4 3 3 2 3 2 2 1 5 2 5 2 1 2 1 5 1 4 1 3 5 5 1 5 2 2 3 1 1 4 3 2 4 5
## [30673] 3 5 3 4 3 1 4 2 2 4 2 2 4 5 3 4 2 2 1 5 1 1 3 2 3 5 3 5 1 3 5 4 2 5 3 4
## [30709] 3 5 1 1 5 5 2 4 1 4 2 4 2 2 3 3 2 3 5 1 3 1 4 3 1 1 3 3 4 2 4 2 2 2 3 1
## [30745] 5 5 5 4 2 5 1 5 5 3 5 1 1 2 2 4 4 5 3 3 3 3 3 2 1 2 4 2 3 1 4 3 4 2 3 1
## [30781] 5 5 4 4 3 3 4 4 4 2 4 3 2 1 5 2 1 3 1 4 4 2 1 1 4 4 1 5 4 3 5 5 3 2 3 2
## [30817] 4 1 1 3 1 1 3 1 3 1 4 4 2 4 2 5 2 5 2 4 4 2 4 3 5 2 5 5 1 4 2 3 5 3 5 4
## [30853] 3 5 5 4 1 5 3 3 2 3 4 4 5 1 2 2 3 1 5 1 3 5 1 4 4 3 3 1 1 2 1 4 4 2 3 5
## [30889] 2 4 5 2 2 3 2 1 4 2 5 2 2 1 1 5 3 3 5 2 1 4 5 5 3 2 3 4 4 4 5 4 2 1 3 5
## [30925] 4 5 2 2 1 2 5 3 1 4 4 1 1 2 2 3 4 1 4 1 5 3 1 1 1 2 3 3 3 3 2 3 5 1 2 2
## [30961] 5 5 1 5 2 2 1 4 3 2 4 1 2 5 4 5 1 3 3 3 2 4 3 3 2 1 3 2 2 1 4 4 2 1 3 1
## [30997] 3 4 2 5 3 1 1 5 2 4 1 2 1 1 2 5 3 1 3 5 5 5 2 4 1 2 1 5 3 5 4 1 5 2 2 2
## [31033] 3 4 4 1 5 4 1 3 5 4 3 4 4 5 5 4 3 3 1 1 4 1 4 5 2 3 2 5 5 1 2 1 1 2 1 3
## [31069] 3 2 3 4 4 1 4 2 4 3 4 5 1 2 2 3 3 2 3 3 3 5 3 3 5 5 2 2 4 3 4 3 2 4 4 1
## [31105] 2 4 2 4 1 3 2 2 1 3 2 5 3 2 1 1 5 2 4 2 5 3 4 1 5 4 4 3 3 1 3 1 1 1 2 2
## [31141] 4 2 5 1 5 3 4 1 5 2 2 5 2 2 2 5 2 4 4 3 5 2 4 1 3 5 3 1 5 4 3 1 5 1 5 2
## [31177] 3 4 4 5 4 2 2 2 1 1 2 5 5 2 5 2 4 5 1 5 4 3 2 1 2 2 1 2 4 2 1 5 1 5 1 5
## [31213] 2 1 1 4 4 3 1 1 3 3 5 5 4 4 5 2 3 3 4 5 1 2 2 1 1 4 4 3 2 4 2 5 3 3 5 1
## [31249] 4 2 1 4 2 2 1 4 3 4 2 5 3 1 2 1 1 1 1 5 5 5 5 5 5 3 4 2 2 2 2 4 2 5 5 5
## [31285] 5 5 2 4 4 3 5 5 4 5 5 1 5 5 1 4 1 4 1 1 1 1 5 3 1 5 1 4 5 2 1 2 1 4 3 4
## [31321] 5 5 5 3 2 3 3 1 5 4 2 4 4 2 2 5 1 2 1 4 1 5 2 5 4 1 4 4 3 2 5 2 1 4 1 3
## [31357] 4 3 1 4 4 5 1 2 2 5 1 2 5 5 4 2 2 5 2 5 3 2 3 2 5 3 3 5 3 2 1 5 2 4 1 2
## [31393] 4 5 3 5 2 3 1 5 4 1 3 3 4 3 3 3 5 5 3 1 5 2 2 2 4 4 4 3 2 1 3 2 3 4 2 1
## [31429] 4 4 1 4 3 5 2 1 4 2 3 2 2 5 2 5 5 4 4 5 4 5 5 2 1 1 1 5 2 5 4 2 2 1 4 4
## [31465] 3 5 2 1 5 2 2 3 2 4 2 5 1 5 3 1 5 3 4 5 2 4 4 3 4 3 2 3 1 5 5 4 3 4 2 2
## [31501] 4 1 5 5 1 5 1 1 4 2 5 5 1 4 5 1 4 2 1 4 3 3 1 3 1 2 1 3 4 1 5 1 3 2 3 1
## [31537] 5 2 2 3 3 4 2 1 1 5 3 1 3 1 4 4 5 2 2 3 5 4 4 3 4 5 4 2 1 5 5 1 4 1 5 1
## [31573] 5 1 4 3 3 1 5 4 2 2 1 5 4 3 5 3 1 1 1 1 4 1 5 4 1 4 3 1 5 4 1 1 1 5 4 2
## [31609] 5 3 3 1 3 4 5 5 2 4 5 2 1 4 5 1 3 3 1 3 2 3 1 1 3 3 4 4 4 5 1 3 4 3 4 2
## [31645] 5 1 2 1 2 4 5 5 5 3 5 2 1 2 5 3 4 4 5 3 2 1 5 4 1 2 3 2 3 1 4 2 3 5 3 1
## [31681] 4 5 1 5 5 4 3 3 2 5 4 3 4 2 2 2 3 5 3 1 1 5 4 1 4 4 2 5 1 4 5 4 1 3 2 1
## [31717] 4 5 1 5 3 5 5 2 4 4 1 1 2 2 3 2 4 5 5 4 4 1 2 5 5 3 5 2 1 4 3 2 1 5 2 5
## [31753] 2 3 4 3 4 4 2 2 4 1 1 5 3 3 3 4 2 4 3 1 2 4 4 2 4 4 2 1 3 2 5 2 3 4 4 5
## [31789] 1 2 5 1 1 5 2 4 2 5 4 5 5 2 1 2 2 4 4 4 1 4 3 1 4 3 5 3 1 2 4 1 4 2 5 5
## [31825] 1 1 3 5 5 1 3 5 5 2 1 3 3 5 4 3 4 4 5 3 3 2 3 5 4 1 3 2 5 3 4 3 3 1 1 2
## [31861] 2 3 4 3 1 2 3 3 4 1 2 3 3 4 4 3 1 4 2 1 2 4 5 4 4 5 2 4 2 3 3 2 1 4 1 1
## [31897] 5 4 1 4 4 5 5 1 3 2 2 1 5 5 3 5 3 1 3 4 5 1 4 4 4 3 5 4 1 4 4 1 1 3 3 5
## [31933] 1 2 5 1 5 5 3 3 2 2 5 5 3 4 5 5 4 2 3 2 5 1 4 2 2 1 5 5 5 1 1 3 4 3 2 4
## [31969] 1 2 2 3 3 4 1 2 1 3 3 2 2 4 2 4 5 1 1 1 5 2 5 3 5 4 1 5 4 4 2 5 4 5 3 1
## [32005] 5 5 4 5 4 1 3 2 5 5 1 3 3 3 2 5 3 3 4 5 2 4 1 4 4 4 3 2 2 1 2 5 5 5 1 1
## [32041] 2 4 5 4 5 5 4 2 1 3 1 5 3 1 4 3 5 1 4 4 2 4 3 3 1 5 3 2 2 2 2 4 2 3 3 5
## [32077] 4 3 5 1 2 1 1 1 2 5 3 1 5 2 3 3 1 2 2 1 1 4 5 5 5 1 3 2 4 4 3 2 3 2 1 4
## [32113] 1 1 5 3 4 1 1 1 3 1 4 4 3 4 1 4 4 3 4 4 5 5 3 1 5 1 5 1 5 3 2 2 5 5 1 3
## [32149] 4 2 3 2 4 1 4 5 4 4 4 4 2 2 4 3 2 4 1 3 1 3 4 3 1 4 2 3 1 4 3 3 4 3 3 3
## [32185] 5 5 2 1 3 1 4 4 3 4 3 4 2 5 4 3 2 4 1 5 5 4 3 3 3 3 2 1 5 4 3 4 1 2 4 2
## [32221] 3 4 4 2 2 1 1 4 3 5 2 5 2 2 3 4 5 4 2 4 3 5 4 4 5 3 2 5 1 3 5 3 5 4 3 3
## [32257] 3 3 3 4 4 1 4 5 2 1 2 2 1 2 1 1 4 5 4 3 4 1 1 4 1 1 1 4 5 3 5 2 4 5 2 2
## [32293] 4 1 3 2 1 2 1 1 2 2 4 2 4 4 3 3 1 4 5 4 5 4 3 2 5 3 2 1 3 5 3 1 3 2 2 1
## [32329] 5 4 5 2 2 1 2 5 3 3 2 2 4 5 2 3 3 3 2 2 4 4 1 1 1 3 3 5 1 3 1 3 4 1 1 2
## [32365] 2 3 4 2 2 3 1 1 4 3 5 1 3 4 5 1 5 5 2 4 2 2 2 3 5 2 5 3 3 4 3 5 3 1 4 4
## [32401] 3 4 3 1 5 4 1 4 2 2 1 1 4 2 3 3 4 2 5 3 5 1 4 4 5 1 3 1 5 1 2 5 5 1 2 1
## [32437] 3 1 2 5 1 2 1 3 5 4 5 4 3 4 5 1 4 3 5 2 2 5 1 2 4 1 5 1 2 3 5 5 4 5 4 5
## [32473] 1 3 5 4 5 2 1 3 1 5 5 3 2 1 2 2 1 3 2 1 1 3 5 4 3 5 5 4 2 1 1 2 1 4 3 4
## [32509] 2 1 1 4 3 5 2 4 4 3 2 3 4 2 3 4 4 1 2 4 3 5 5 5 4 1 4 1 1 5 4 1 5 1 3 1
## [32545] 5 1 3 4 5 2 3 5 3 4 3 2 1 5 3 2 1 2 4 1 2 1 3 1 4 3 4 2 2 1 1 3 4 4 5 5
## [32581] 5 4 3 4 3 5 4 3 1 1 3 5 2 4 3 3 5 1 4 4 1 1 4 3 1 1 2 5 1 4 1 3 5 5 3 3
## [32617] 4 3 4 3 2 5 5 5 1 1 3 3 2 4 3 4 2 1 2 4 5 4 5 2 5 4 4 5 2 3 3 5 4 5 1 4
## [32653] 3 4 5 1 4 3 5 1 1 2 2 4 5 4 4 2 2 2 3 5 3 1 1 1 1 4 3 3 5 3 1 2 2 3 3 2
## [32689] 1 3 5 3 2 4 4 5 4 3 3 5 3 4 1 3 2 5 1 3 1 1 1 1 2 3 5 1 3 5 4 4 1 5 2 2
## [32725] 5 5 2 5 1 4 2 1 4 4 2 4 2 4 2 1 3 5 4 2 4 5 5 2 4 5 5 3 3 1 4 4 4 2 4 4
## [32761] 4 1 3 3 5 1 3 4 3 2 5 1 3 3 1 2 5 1 3 5 5 4 1 5 4 1 2 5 4 3 4 2 4 2 5 4
## [32797] 5 5 5 4 5 3 4 5 2 2 3 4 2 3 3 3 3 2 4 3 2 5 3 5 3 1 4 2 2 3 1 5 1 1 5 1
## [32833] 3 2 3 5 4 1 5 1 3 5 3 5 3 1 1 2 4 4 3 3 3 1 4 5 2 3 5 1 2 2 1 3 4 3 3 1
## [32869] 4 5 5 2 5 1 2 5 2 4 1 5 2 5 1 3 1 5 2 3 5 4 5 4 3 5 1 2 3 2 2 3 1 3 3 1
## [32905] 2 4 2 2 2 5 5 5 1 4 3 2 2 3 5 5 2 3 2 1 4 3 2 3 2 5 5 4 3 2 1 4 5 5 3 4
## [32941] 5 5 2 2 4 2 1 3 3 3 2 1 2 2 2 5 2 3 3 5 4 1 5 4 5 1 1 4 4 4 2 1 5 1 3 1
## [32977] 5 3 3 2 4 4 4 5 5 3 1 2 3 2 1 2 4 4 1 3 4 5 1 1 5 5 4 5 1 5 1 3 1 3 3 3
## [33013] 1 5 5 2 5 5 4 1 5 5 2 1 3 4 2 5 4 1 4 4 4 3 2 5 1 4 4 5 2 2 2 3 4 5 3 3
## [33049] 5 4 4 4 3 2 3 5 2 5 1 1 1 4 5 4 5 3 5 3 1 5 4 4 3 5 2 2 1 3 2 3 5 2 1 3
## [33085] 2 2 4 1 4 4 3 3 1 2 4 2 1 1 3 5 1 1 3 3 4 5 1 3 2 5 3 2 1 4 2 2 2 2 1 4
## [33121] 4 3 3 1 4 2 1 4 2 3 5 2 4 3 3 4 2 1 3 4 3 2 4 4 1 1 4 1 2 5 2 5 3 5 4 4
## [33157] 1 4 4 3 4 4 2 5 1 2 3 5 5 1 2 2 1 2 2 1 3 2 3 1 5 5 4 4 3 1 4 4 3 5 5 4
## [33193] 3 2 4 4 2 5 2 2 1 5 4 2 2 1 5 1 2 4 5 4 2 5 3 2 5 4 1 1 2 1 5 3 1 3 5 2
## [33229] 4 5 3 5 1 4 3 3 3 1 3 1 3 3 1 2 5 5 3 4 4 1 1 1 5 5 2 3 2 4 5 1 5 5 5 5
## [33265] 4 5 3 3 3 5 3 5 3 1 2 3 2 4 2 5 5 2 3 3 1 3 4 4 3 4 5 3 1 2 3 4 1 4 1 2
## [33301] 5 5 2 1 1 2 2 2 2 2 2 5 4 4 1 3 5 4 2 1 1 1 1 4 2 3 5 4 2 5 1 5 1 1 1 2
## [33337] 3 5 1 3 5 4 1 4 4 1 3 4 4 4 1 2 2 5 1 2 3 3 1 1 5 3 5 4 1 5 2 2 1 4 4 1
## [33373] 3 3 4 4 5 2 3 5 5 4 5 1 2 5 1 3 2 5 1 5 2 2 5 1 4 3 1 3 3 5 3 3 4 5 1 3
## [33409] 5 1 4 4 5 3 2 2 5 1 2 5 3 5 2 2 5 3 4 3 2 3 2 1 5 4 2 1 5 5 1 2 3 3 5 3
## [33445] 3 5 3 4 5 2 2 3 3 1 2 1 4 3 3 1 2 2 3 4 1 2 3 4 5 2 5 1 2 2 5 4 1 1 3 3
## [33481] 5 4 3 2 4 1 4 4 2 3 1 3 4 2 4 3 2 4 4 1 3 2 2 3 5 1 1 3 4 4 3 5 4 5 3 1
## [33517] 3 5 1 2 4 5 4 1 3 5 1 3 1 2 2 4 2 4 1 4 1 5 2 3 4 5 1 2 3 1 2 1 2 4 2 3
## [33553] 2 2 5 3 1 5 5 4 4 4 5 4 3 5 5 1 4 4 1 2 2 1 5 5 2 3 1 3 4 5 5 2 4 4 1 4
## [33589] 2 5 1 3 1 4 2 2 1 5 5 2 4 4 5 4 3 2 5 1 1 1 3 4 2 1 4 3 5 3 4 4 3 1 3 1
## [33625] 3 4 4 2 5 3 3 3 1 2 1 4 3 2 4 2 3 3 1 2 3 2 1 5 5 5 1 4 4 2 1 4 4 1 3 5
## [33661] 1 4 5 4 2 2 4 3 5 1 3 4 4 3 2 5 5 3 4 1 4 1 2 4 4 2 1 5 1 1 2 4 5 3 3 5
## [33697] 5 2 4 5 1 2 4 4 3 3 3 1 4 5 1 3 4 1 3 3 2 2 2 4 2 1 1 5 3 2 3 1 2 3 1 2
## [33733] 5 4 3 1 2 5 4 1 4 2 3 2 1 1 2 5 3 5 2 5 5 2 5 2 1 4 1 1 5 5 1 5 3 3 3 3
## [33769] 4 5 4 4 1 5 4 2 5 1 3 4 3 4 5 1 1 5 3 1 3 3 3 2 5 4 3 4 2 5 4 2 3 2 3 2
## [33805] 3 3 2 1 4 1 1 2 1 2 4 3 1 2 3 1 2 1 4 5 4 3 5 3 3 5 5 5 2 4 3 2 2 4 2 3
## [33841] 3 4 3 5 4 1 1 4 3 2 3 4 5 3 2 5 5 3 4 3 4 2 4 3 2 5 1 2 4 4 5 3 3 1 2 4
## [33877] 2 5 2 3 4 5 3 1 5 5 4 2 5 3 1 5 3 1 1 5 3 3 2 3 4 4 4 5 3 1 1 3 5 1 5 4
## [33913] 2 3 1 3 3 3 3 2 5 2 1 4 5 4 4 1 5 2 3 2 1 5 2 1 3 4 2 4 2 1 4 1 3 4 1 2
## [33949] 5 5 4 4 1 5 1 4 1 3 2 1 5 4 2 3 1 1 3 1 2 2 4 1 3 4 1 3 4 5 1 4 4 4 3 4
## [33985] 1 4 5 3 1 3 1 1 4 2 4 5 5 2 4 5 5 1 3 2 4 1 5 5 5 3 2 4 2 5 3 3 1 5 3 2
## [34021] 4 2 3 3 4 1 2 2 3 1 3 4 3 4 5 4 1 4 2 4 1 4 2 4 5 4 3 4 3 2 5 2 2 4 5 5
## [34057] 2 1 4 5 1 1 2 2 5 3 5 5 1 3 3 3 4 4 2 1 3 1 1 3 3 4 2 4 4 4 4 1 4 2 4 3
## [34093] 2 4 3 3 4 3 2 5 5 4 1 5 4 2 2 4 2 3 3 3 1 5 5 1 1 5 2 5 5 2 4 4 2 5 2 3
## [34129] 4 3 5 2 2 3 3 1 4 4 4 3 2 2 3 2 1 2 2 1 3 3 4 5 1 3 3 1 3 1 3 4 2 3 5 2
## [34165] 1 5 3 5 4 5 4 4 1 5 2 1 5 5 3 4 5 1 1 2 2 1 1 5 1 5 1 1 3 4 3 2 4 5 5 2
## [34201] 3 1 5 5 2 4 1 1 2 2 2 1 5 4 3 2 4 4 3 1 3 3 1 1 5 3 1 5 4 2 1 1 4 4 2 5
## [34237] 1 4 1 5 5 3 2 2 3 4 5 3 2 1 1 5 4 4 2 1 3 2 1 5 3 3 5 2 5 3 5 4 4 5 2 1
## [34273] 2 1 2 4 1 5 3 3 3 2 1 2 5 2 1 5 2 4 4 3 3 4 4 3 5 1 5 1 2 4 1 4 4 3 1 1
## [34309] 5 5 5 4 4 1 4 4 5 5 3 3 5 5 4 1 1 5 1 1 1 4 4 5 3 1 3 1 1 1 5 2 1 3 5 5
## [34345] 3 5 2 4 2 1 2 1 5 3 2 2 2 3 5 3 5 4 5 3 5 2 3 2 1 2 1 2 3 5 4 1 4 1 5 1
## [34381] 4 5 2 4 4 3 3 1 1 3 5 1 4 3 3 1 4 3 4 2 4 4 2 5 5 1 1 5 3 3 1 1 4 4 1 4
## [34417] 3 1 1 5 1 5 1 4 2 4 4 2 5 2 1 4 3 4 4 2 4 5 4 3 4 5 3 2 4 4 5 1 4 1 4 3
## [34453] 5 1 3 3 3 4 5 1 4 4 3 4 4 3 2 2 3 3 4 4 4 3 2 4 4 4 5 2 3 4 3 3 1 5 5 1
## [34489] 1 1 3 4 2 3 2 2 4 3 4 1 2 1 1 4 5 2 4 2 1 2 1 3 3 5 2 5 2 2 1 1 5 1 5 5
## [34525] 5 1 2 5 3 4 4 3 4 4 1 1 4 3 5 1 2 5 2 3 1 5 4 5 4 1 2 5 4 3 4 2 2 2 4 1
## [34561] 2 1 1 2 4 5 4 4 4 5 4 5 5 4 4 3 3 2 2 4 2 5 2 2 5 2 4 2 3 2 3 3 1 1 5 2
## [34597] 5 1 3 4 5 4 5 3 2 5 4 2 2 3 1 2 5 2 1 4 5 2 3 2 2 3 1 5 4 3 5 4 3 4 3 5
## [34633] 3 1 3 4 4 1 2 3 2 4 5 3 3 2 5 1 2 2 4 2 3 5 5 2 1 2 4 3 3 4 4 2 1 2 5 4
## [34669] 1 3 4 1 3 2 1 5 4 2 3 5 5 1 2 4 2 4 1 3 3 3 5 4 4 2 1 1 3 5 5 4 3 1 5 4
## [34705] 3 2 1 5 3 4 3 5 3 1 4 2 4 5 1 2 5 2 2 3 3 3 4 4 5 2 3 2 5 2 5 5 2 5 1 2
## [34741] 3 2 5 1 4 2 1 2 3 2 2 1 5 1 2 3 1 4 1 3 3 2 4 4 4 5 1 4 3 5 1 1 2 5 2 3
## [34777] 4 3 5 1 1 2 5 2 5 3 5 2 2 5 5 4 1 4 3 5 5 5 4 2 5 3 2 2 2 2 5 5 5 1 2 5
## [34813] 2 5 4 4 5 3 3 1 5 5 4 5 4 1 1 2 5 3 2 3 3 2 5 2 4 5 1 4 3 2 2 4 2 2 2 1
## [34849] 4 5 2 1 4 3 5 2 1 4 5 5 3 2 3 2 4 5 3 2 2 4 2 2 1 3 4 5 5 3 3 5 4 4 2 2
## [34885] 5 4 1 1 2 2 2 5 5 5 5 5 4 4 2 5 1 4 3 3 3 2 2 5 5 3 2 1 5 3 2 3 5 1 3 2
## [34921] 1 2 5 1 1 4 5 2 1 5 1 2 4 1 1 4 3 1 1 3 2 5 1 3 2 5 4 2 4 3 5 5 2 4 5 3
## [34957] 4 4 1 5 5 1 4 4 1 3 3 2 1 5 2 3 1 5 1 3 4 1 4 3 1 5 2 3 2 5 1 3 2 2 2 2
## [34993] 4 3 4 3 5 1 3 1 1 1 4 2 4 2 3 4 2 3 1 1 2 2 1 3 5 5 5 4 2 3 3 3 5 1 4 3
## [35029] 5 3 2 2 5 1 3 4 2 3 5 5 2 4 1 3 4 1 4 1 5 2 5 1 4 4 1 2 5 2 1 4 2 3 1 5
## [35065] 3 4 4 5 5 4 2 1 4 5 2 2 5 4 5 5 2 1 5 4 3 3 3 2 2 1 2 2 2 5 1 1 4 5 4 4
## [35101] 5 1 4 3 3 3 2 5 3 4 5 3 5 2 3 4 3 1 1 4 2 1 1 4 1 2 5 1 2 5 2 3 3 1 2 2
## [35137] 4 4 5 4 2 5 5 5 2 3 4 4 1 3 4 3 1 1 2 2 2 1 1 5 2 5 4 3 4 1 4 5 4 4 3 5
## [35173] 3 5 2 5 3 5 5 1 1 4 3 4 4 5 3 3 3 5 5 4 1 1 5 1 3 1 4 5 5 2 1 3 1 2 1 4
## [35209] 2 3 5 4 2 2 2 3 3 5 4 5 5 4 3 2 5 1 4 4 4 2 5 3 2 5 2 1 5 3 4 3 2 5 2 5
## [35245] 1 3 5 4 2 2 4 2 4 2 3 4 3 5 2 4 4 1 4 2 4 1 3 2 1 5 4 2 4 3 3 1 5 2 4 5
## [35281] 2 5 3 3 1 1 4 2 1 1 3 2 5 4 4 2 5 1 3 2 2 1 4 2 4 2 4 1 5 3 5 1 1 4 5 1
## [35317] 1 3 5 3 5 1 1 5 5 4 5 1 3 2 2 1 3 5 5 4 5 4 5 3 1 4 4 4 2 2 1 3 1 3 5 1
## [35353] 3 2 5 5 5 3 3 4 2 4 5 2 1 4 4 5 1 3 1 4 1 5 1 5 1 5 2 2 4 1 3 1 3 1 4 4
## [35389] 4 3 4 5 3 3 2 5 1 2 5 5 5 4 2 5 4 4 3 5 2 3 1 4 3 1 1 4 1 3 1 1 2 4 1 5
## [35425] 5 3 3 4 1 4 4 3 1 4 2 3 2 5 2 3 4 3 3 2 4 1 2 1 3 5 1 4 2 1 2 2 5 1 4 3
## [35461] 1 3 3 5 1 4 2 2 3 4 5 2 5 3 5 5 4 5 1 3 2 5 3 1 4 5 4 4 1 5 5 5 5 5 5 5
## [35497] 3 3 3 2 3 2 1 2 1 3 3 1 1 5 1 1 4 3 3 2 3 5 2 1 3 2 3 2 5 2 4 1 1 1 1 3
## [35533] 5 5 4 3 3 4 5 5 2 5 4 5 3 4 1 5 3 3 5 2 5 1 5 2 2 4 1 2 5 5 3 5 4 5 4 3
## [35569] 4 5 5 1 4 3 1 2 2 1 4 2 3 5 2 1 2 5 4 4 4 1 2 5 3 3 3 3 2 5 1 1 1 5 2 3
## [35605] 5 5 2 3 2 5 5 5 4 1 3 2 4 4 5 5 3 5 5 3 1 3 4 4 1 2 3 1 5 2 2 3 3 4 3 1
## [35641] 2 2 3 5 3 5 5 3 2 5 3 5 5 5 1 2 4 5 4 4 2 3 3 2 2 5 1 2 1 1 5 1 1 2 2 4
## [35677] 2 4 5 3 5 2 1 5 3 1 2 4 4 3 2 2 4 2 3 3 2 1 3 3 3 1 3 4 4 1 5 2 4 3 5 2
## [35713] 1 2 1 2 1 4 3 5 1 4 1 2 1 2 3 3 1 1 5 3 3 4 5 2 3 5 4 4 2 1 2 4 5 4 2 1
## [35749] 4 4 2 5 2 5 3 5 4 2 3 3 3 5 5 2 3 3 3 2 1 5 2 1 3 2 5 1 4 1 5 5 1 3 1 5
## [35785] 4 2 2 4 3 3 1 1 2 1 2 1 5 2 4 3 4 3 3 1 2 2 2 3 4 4 1 3 5 1 1 3 4 1 3 1
## [35821] 3 4 3 3 2 5 2 5 5 3 5 1 1 5 2 4 1 3 1 3 5 5 5 3 4 3 5 4 1 5 5 2 5 5 5 3
## [35857] 5 3 4 5 4 4 1 5 5 1 2 1 3 4 1 2 1 3 4 3 5 4 4 1 1 5 5 1 5 4 2 5 5 1 1 4
## [35893] 2 3 2 5 3 5 5 3 5 4 2 4 2 3 3 5 3 1 2 3 3 1 1 5 4 3 1 5 1 1 1 2 4 3 1 4
## [35929] 2 2 2 4 4 3 2 3 3 5 4 2 4 4 5 5 3 1 4 1 2 4 5 2 2 5 4 4 5 2 3 2 1 2 1 3
## [35965] 3 2 3 1 2 5 4 5 4 1 1 5 5 2 2 5 5 1 1 2 5 2 5 5 2 2 2 3 5 4 3 4 5 5 4 4
## [36001] 1 4 2 3 1 5 5 4 5 2 2 1 1 2 1 4 5 1 1 1 4 2 5 5 4 4 2 1 2 1 2 2 1 1 2 1
## [36037] 5 1 2 1 2 5 1 5 4 4 4 4 5 2 5 3 4 5 1 3 5 4 2 3 4 1 1 1 2 1 5 4 1 3 5 1
## [36073] 2 1 5 4 5 1 4 2 2 2 2 1 5 4 1 4 1 3 1 3 3 3 4 5 1 4 3 3 5 3 3 2 5 4 4 4
## [36109] 2 4 3 3 1 5 1 3 5 3 3 2 4 4 4 3 1 4 4 2 4 1 2 1 5 1 4 5 5 4 2 5 1 1 2 3
## [36145] 5 4 5 2 2 4 3 3 3 5 4 3 4 1 3 5 1 4 2 3 2 5 5 3 1 4 1 1 1 5 4 5 4 3 2 3
## [36181] 2 4 4 1 3 1 2 1 4 3 5 2 3 3 4 3 5 3 5 5 5 5 4 1 2 2 4 2 4 4 1 2 2 2 4 5
## [36217] 2 2 2 1 4 2 5 1 3 3 5 2 1 3 2 5 2 4 2 3 4 1 4 1 4 5 3 3 3 1 5 4 2 5 2 4
## [36253] 5 2 3 4 1 5 2 5 1 1 5 2 1 4 3 2 5 4 1 3 5 2 3 3 5 3 1 4 4 5 5 2 2 4 4 1
## [36289] 5 3 5 2 4 3 5 4 3 4 1 5 4 4 1 5 4 4 3 3 5 2 5 4 4 5 3 1 1 5 4 4 5 5 2 4
## [36325] 5 4 1 1 2 1 1 3 5 4 1 1 3 3 2 1 3 2 3 2 3 2 3 3 5 2 1 1 4 1 2 4 5 4 2 4
## [36361] 3 1 2 4 2 3 1 3 1 3 5 5 5 3 2 4 3 2 5 3 5 5 2 2 4 1 4 1 2 3 1 5 4 3 3 3
## [36397] 3 2 5 3 4 1 1 1 2 4 3 1 3 5 3 4 5 1 4 1 2 1 3 4 1 2 1 2 5 1 1 1 3 1 1 4
## [36433] 4 3 5 3 4 4 1 3 1 1 2 5 1 2 2 1 1 5 1 5 5 2 1 5 2 3 4 2 1 1 1 4 3 4 2 5
## [36469] 1 4 1 2 5 4 4 2 5 1 4 3 5 2 4 4 4 2 2 5 1 2 2 5 5 3 5 4 3 2 5 2 5 1 3 4
## [36505] 3 4 5 5 1 5 2 1 2 4 4 2 5 3 5 4 1 3 2 2 3 1 3 2 2 1 2 2 3 5 2 4 4 3 4 4
## [36541] 1 1 4 4 4 5 4 1 5 2 3 1 5 5 5 4 1 3 2 4 2 3 1 5 5 2 3 4 2 4 3 1 3 2 4 5
## [36577] 2 5 5 4 3 5 1 2 5 5 2 4 2 3 3 4 4 1 3 1 4 1 2 4 2 3 4 1 4 3 3 5 1 5 5 2
## [36613] 1 3 4 4 1 2 3 5 3 5 3 2 2 5 4 2 5 1 2 1 1 1 2 3 1 2 2 2 5 2 3 2 1 5 3 1
## [36649] 4 3 2 3 1 3 1 4 3 2 3 1 2 4 2 5 4 5 4 2 1 2 5 3 1 1 2 4 4 3 4 2 5 4 3 1
## [36685] 2 4 4 1 2 4 5 4 4 1 2 2 1 4 1 3 3 4 5 2 2 3 5 3 5 3 2 1 3 5 2 2 3 1 1 2
## [36721] 3 5 1 2 5 4 3 2 5 1 2 3 4 4 4 2 5 1 5 5 3 5 5 2 4 2 5 4 4 1 2 3 4 3 1 4
## [36757] 1 3 2 3 2 2 2 1 5 2 1 1 5 1 2 2 1 1 5 5 2 4 1 1 2 3 1 5 5 5 5 2 5 1 4 3
## [36793] 4 3 4 1 4 4 2 1 4 5 2 2 3 1 4 4 1 1 3 1 2 5 4 1 3 4 5 4 4 1 1 1 5 1 4 1
## [36829] 2 4 1 5 1 5 5 4 2 4 5 4 4 3 1 5 2 5 3 3 4 2 2 2 1 4 1 4 1 4 3 3 2 4 2 3
## [36865] 4 5 2 4 2 2 3 5 2 1 2 5 3 1 2 5 2 4 2 4 1 1 2 3 2 3 2 4 1 2 1 2 3 5 2 3
## [36901] 3 1 2 5 5 5 3 4 4 4 3 4 5 5 5 1 2 1 4 5 5 5 4 3 3 3 1 3 3 4 5 4 5 2 4 2
## [36937] 1 4 3 5 4 1 2 1 3 5 3 4 4 3 4 2 1 4 2 5 3 4 1 3 2 2 3 2 2 4 3 3 3 5 5 5
## [36973] 4 1 3 5 5 3 3 3 5 3 2 4 4 4 1 1 4 2 3 1 2 4 5 4 2 2 5 2 2 2 4 4 3 3 3 3
## [37009] 2 5 2 1 5 5 3 2 4 1 3 3 4 5 4 5 2 4 5 1 5 4 3 5 1 5 3 3 3 3 2 1 1 4 2 2
## [37045] 2 4 2 4 2 4 1 4 5 3 4 3 3 4 2 3 5 4 2 4 5 2 3 3 1 4 2 2 2 4 5 4 2 4 2 2
## [37081] 4 2 1 5 4 4 3 4 2 3 1 3 3 3 3 2 5 3 4 3 1 4 5 3 3 1 3 5 4 3 3 5 4 5 4 5
## [37117] 4 4 5 1 1 4 1 1 2 1 5 5 5 5 1 4 5 1 3 4 2 1 5 5 1 3 1 5 4 5 2 3 4 5 2 1
## [37153] 4 3 5 3 3 5 1 1 4 5 5 2 4 4 3 2 4 2 5 5 4 2 3 3 1 4 4 3 2 1 2 3 5 5 1 3
## [37189] 5 2 5 4 3 5 5 5 4 1 2 4 3 2 4 5 2 5 2 2 1 3 1 1 1 2 3 2 5 1 1 3 3 5 1 1
## [37225] 4 5 1 2 3 3 3 5 2 1 3 2 1 4 1 3 4 4 1 3 3 3 2 3 1 2 1 5 4 3 1 4 4 5 5 4
## [37261] 5 1 2 2 4 5 2 4 1 5 4 5 5 5 1 2 1 1 4 3 2 1 1 2 3 2 2 5 1 5 3 2 3 4 4 3
## [37297] 4 1 1 4 1 5 2 3 3 3 2 2 2 2 4 1 3 2 4 5 3 5 1 2 3 4 2 1 5 3 3 3 2 3 2 2
## [37333] 4 4 1 4 2 3 4 3 4 5 3 4 1 3 1 3 5 1 5 4 5 3 3 4 3 4 1 3 5 3 5 3 3 3 5 4
## [37369] 5 3 4 5 3 4 4 3 4 3 1 2 5 2 2 2 2 1 1 1 2 4 5 5 5 5 3 2 3 1 1 2 2 4 4 4
## [37405] 2 3 2 2 5 4 5 1 3 5 1 5 1 3 2 4 4 2 4 1 2 5 2 3 1 1 3 5 5 2 4 5 3 4 5 2
## [37441] 4 3 1 4 3 1 3 2 2 1 4 1 3 4 2 3 3 5 4 4 1 3 5 3 4 3 1 1 2 5 3 4 1 4 1 1
## [37477] 4 2 2 5 5 2 1 3 1 5 4 3 2 1 2 3 2 2 2 5 1 2 5 3 4 5 5 3 2 2 2 2 2 2 5 5
## [37513] 1 4 1 4 3 1 5 1 2 3 4 1 4 4 1 5 2 2 5 2 1 1 3 3 4 5 2 5 1 1 3 4 2 4 2 5
## [37549] 2 1 2 3 3 5 4 3 2 3 5 3 2 5 1 4 3 4 2 2 4 2 3 2 3 2 4 5 3 3 4 3 3 4 1 5
## [37585] 3 5 2 2 4 4 4 3 4 3 5 3 5 4 5 4 1 2 4 3 1 5 3 5 4 3 1 3 4 4 1 4 5 2 5 3
## [37621] 4 4 4 4 1 5 4 4 4 2 2 5 1 2 4 4 2 1 3 1 5 3 4 3 1 1 5 3 1 2 2 1 4 1 5 5
## [37657] 5 5 2 4 2 1 2 1 4 3 3 2 4 3 2 3 3 5 5 4 3 1 2 2 1 3 2 5 2 4 1 2 5 1 2 4
## [37693] 2 4 3 5 5 1 3 3 3 5 2 5 2 4 3 2 5 3 1 3 2 3 4 3 3 3 1 2 5 3 1 5 5 3 3 4
## [37729] 4 4 2 4 5 5 1 4 4 2 5 2 5 3 1 5 5 1 5 2 2 1 2 2 3 5 5 2 5 2 5 5 3 1 5 5
## [37765] 5 5 3 3 4 2 2 5 2 1 5 3 2 3 5 2 1 1 2 1 2 5 3 3 1 1 1 5 5 2 2 1 1 1 5 5
## [37801] 2 4 5 5 5 5 2 2 5 4 4 3 3 3 5 1 2 2 1 4 5 2 3 5 2 2 4 2 5 5 3 2 4 5 5 3
## [37837] 3 1 4 3 2 3 2 3 2 4 5 4 3 4 5 1 1 3 4 4 5 3 3 5 4 5 5 3 5 4 3 1 1 2 2 3
## [37873] 5 3 2 5 5 3 4 4 1 5 3 2 3 2 4 1 5 2 2 3 4 3 1 2 3 5 1 4 5 2 5 2 3 5 1 1
## [37909] 3 5 3 3 3 1 5 3 2 5 1 4 4 2 4 5 4 1 2 2 4 5 3 3 2 1 2 4 3 4 5 1 1 1 5 2
## [37945] 2 5 1 3 4 3 1 5 3 4 1 2 1 3 5 3 3 2 3 2 2 1 1 1 1 2 1 3 4 5 3 4 5 1 2 5
## [37981] 1 2 1 3 4 2 4 1 1 2 1 3 2 3 5 2 3 1 2 1 3 1 1 3 2 3 3 4 1 3 5 1 1 1 3 1
## [38017] 5 4 4 4 1 1 2 2 4 3 3 3 3 3 2 2 4 3 3 2 2 3 3 4 2 4 1 3 2 2 5 4 4 4 2 1
## [38053] 2 1 1 3 4 1 3 2 5 4 1 2 3 4 3 3 2 5 4 1 4 2 4 5 1 3 4 2 3 4 2 5 1 2 1 1
## [38089] 1 4 2 2 1 5 2 1 4 4 5 5 2 3 4 5 2 5 1 2 3 2 1 1 2 5 2 4 2 3 5 1 2 5 2 1
## [38125] 3 1 3 3 1 5 1 1 1 1 4 3 1 1 5 2 5 3 2 4 1 3 1 4 5 4 5 5 3 3 3 2 5 1 2 4
## [38161] 1 5 2 1 5 2 2 1 4 2 1 2 5 5 4 2 5 1 2 2 5 5 4 2 2 5 1 4 2 4 4 5 5 3 3 1
## [38197] 3 1 1 4 2 1 4 5 3 5 4 4 2 3 5 4 4 5 1 4 3 4 2 2 5 2 2 4 1 2 1 1 4 5 4 2
## [38233] 3 3 3 2 3 4 1 4 1 3 5 3 2 5 5 1 3 5 3 4 5 5 2 5 2 3 1 3 2 1 5 2 3 5 4 4
## [38269] 2 2 1 2 4 3 1 4 4 5 1 2 2 2 4 1 5 5 4 3 3 3 2 2 1 2 2 2 2 5 3 1 2 3 3 2
## [38305] 5 3 5 3 5 4 2 5 3 3 2 5 4 1 5 1 2 3 2 3 5 5 2 3 4 3 2 3 3 3 5 5 1 5 1 2
## [38341] 1 1 5 5 4 1 5 1 4 4 5 5 3 5 4 2 2 5 2 2 4 2 4 5 4 4 3 2 2 5 3 2 3 1 5 4
## [38377] 1 3 3 3 1 1 3 1 1 1 2 2 3 2 3 1 4 4 5 5 4 5 3 5 1 2 4 2 4 4 5 1 2 1 3 4
## [38413] 1 3 4 3 4 1 2 2 5 2 2 3 5 3 4 4 1 3 4 5 5 3 2 3 2 2 5 5 5 1 2 1 1 5 5 3
## [38449] 3 4 2 4 2 2 5 4 1 4 3 3 5 3 1 3 5 3 5 5 3 2 2 5 1 1 2 1 1 3 4 3 1 2 1 5
## [38485] 5 3 5 3 4 2 4 5 4 4 4 4 5 1 3 4 1 3 2 1 4 2 2 5 1 1 2 1 5 5 3 1 1 4 2 1
## [38521] 3 2 4 1 2 4 4 5 1 5 3 5 4 5 4 4 4 3 2 2 5 2 3 4 2 4 4 3 2 3 3 1 5 5 5 1
## [38557] 1 3 4 4 5 5 2 4 3 3 1 2 2 4 2 3 4 2 3 5 1 4 5 4 4 1 4 4 3 3 1 5 3 1 5 2
## [38593] 1 3 4 1 5 4 2 5 2 1 1 5 3 2 1 4 4 4 4 1 3 4 1 2 4 2 3 2 1 2 5 1 2 5 4 4
## [38629] 2 1 2 1 4 2 2 4 2 1 4 2 5 1 1 4 4 3 3 4 2 3 5 5 4 5 5 3 1 3 1 3 2 2 1 1
## [38665] 3 1 5 3 3 5 1 1 1 4 4 2 2 5 5 5 2 2 4 1 2 5 2 1 3 1 4 2 1 3 3 1 4 3 1 2
## [38701] 5 1 3 3 5 3 1 5 3 1 1 2 5 1 5 2 1 5 2 5 3 2 4 1 4 1 5 1 1 4 3 5 4 2 2 1
## [38737] 1 3 4 3 5 4 2 5 2 3 3 2 1 4 3 3 1 4 2 4 4 5 1 5 1 5 2 4 3 4 2 5 2 1 1 1
## [38773] 1 5 2 2 4 1 3 4 5 1 5 4 3 3 4 5 3 5 5 2 5 5 4 2 1 1 1 1 5 4 3 5 4 4 1 5
## [38809] 5 5 5 1 1 5 2 2 2 5 1 4 4 3 4 2 4 2 1 4 2 3 4 1 2 2 1 1 4 1 2 2 5 4 5 5
## [38845] 4 5 1 5 3 3 4 4 5 3 3 2 1 4 4 1 5 3 5 3 3 3 2 1 2 4 2 4 1 4 1 3 2 1 2 5
## [38881] 2 4 5 1 2 4 2 5 5 4 1 3 4 4 5 3 3 2 1 1 2 3 4 5 5 4 1 1 1 1 2 4 1 2 1 2
## [38917] 2 4 2 1 1 2 5 3 5 4 3 2 1 3 1 5 2 3 5 2 1 5 2 3 4 4 3 3 3 2 1 2 1 5 1 3
## [38953] 1 3 2 4 1 2 1 3 4 3 2 2 3 5 3 1 3 1 2 1 1 4 2 4 3 4 2 3 1 4 3 3 3 2 5 3
## [38989] 1 4 4 5 1 3 2 4 3 4 1 2 4 2 1 4 1 4 5 2 1 2 4 5 2 5 1 1 4 1 2 1 1 1 2 2
## [39025] 5 2 5 2 3 1 2 2 4 1 5 1 3 2 4 4 1 2 1 3 5 2 2 5 1 2 4 1 5 4 5 5 4 4 3 1
## [39061] 4 4 5 1 2 1 5 5 4 1 5 2 5 3 5 3 1 1 1 3 5 2 1 4 5 3 4 5 5 4 4 3 1 1 3 2
## [39097] 3 2 3 2 4 3 1 3 5 1 4 1 4 3 1 3 5 1 3 3 1 4 3 5 4 5 5 5 1 3 2 4 3 3 2 2
## [39133] 5 3 4 5 2 2 4 1 1 5 2 3 2 3 4 4 4 5 5 3 1 5 3 2 2 1 3 1 2 4 2 4 2 1 2 1
## [39169] 2 1 3 4 1 3 5 2 5 5 2 1 2 2 4 5 2 4 4 1 4 3 3 2 3 3 3 3 5 4 4 1 4 4 4 1
## [39205] 1 1 1 2 4 1 2 4 4 3 2 4 4 4 1 1 5 5 4 5 3 4 2 4 4 3 5 2 2 2 1 2 5 2 4 2
## [39241] 3 5 1 5 4 4 4 4 2 1 1 3 4 3 4 2 3 4 4 5 2 4 1 2 4 3 5 1 3 2 2 1 3 3 2 3
## [39277] 2 1 4 2 3 4 2 3 5 2 4 2 1 2 3 2 2 4 4 1 5 3 5 1 1 1 2 4 3 1 2 2 2 1 2 4
## [39313] 3 2 5 3 5 3 4 4 1 4 5 4 3 1 1 5 2 3 3 3 4 5 1 5 4 1 2 1 1 2 5 2 2 3 1 2
## [39349] 4 1 5 1 2 4 4 5 2 3 3 1 2 2 3 3 3 5 3 5 5 4 4 1 3 2 5 4 2 4 2 2 5 2 3 1
## [39385] 4 5 4 3 2 1 2 5 4 1 5 1 3 1 2 3 2 1 1 3 1 3 3 2 3 5 1 3 5 4 5 2 4 1 3 5
## [39421] 4 2 3 1 3 1 4 3 2 4 2 2 5 2 2 3 4 1 3 3 2 2 1 3 4 4 3 2 3 1 4 5 3 4 1 3
## [39457] 1 2 3 3 2 5 5 4 1 1 3 2 5 4 1 4 3 3 5 4 4 2 1 4 4 2 5 5 4 5 5 3 1 2 1 3
## [39493] 1 1 5 2 5 5 3 4 4 2 4 3 1 1 3 1 2 3 5 3 2 2 1 5 1 1 5 2 4 1 5 3 5 2 4 4
## [39529] 4 3 4 4 5 1 1 1 5 1 1 2 2 2 1 2 2 4 5 4 3 4 2 5 4 5 2 2 1 1 3 3 5 2 1 1
## [39565] 3 1 3 5 1 4 2 3 1 4 2 3 5 1 3 5 4 2 2 4 1 3 4 1 2 3 2 3 4 3 4 2 4 2 5 2
## [39601] 4 4 1 5 4 3 3 1 3 1 5 3 5 5 3 5 4 2 1 1 4 5 3 3 5 2 3 4 2 4 2 4 4 5 1 5
## [39637] 2 3 1 5 1 2 2 1 5 2 1 5 5 3 1 4 5 4 5 2 4 4 5 4 3 3 4 3 1 5 4 1 5 2 3 3
## [39673] 4 1 2 1 3 3 5 2 2 3 2 5 4 3 3 3 2 1 3 3 2 2 4 4 1 3 3 5 4 3 5 3 4 3 4 5
## [39709] 2 4 2 2 2 1 4 3 1 4 1 3 2 4 5 1 3 3 3 2 1 1 5 1 1 1 1 1 3 4 4 4 2 4 5 2
## [39745] 5 5 5 1 3 5 1 1 4 1 4 2 1 4 3 1 5 1 3 4 5 5 3 3 4 5 3 1 4 2 2 2 3 5 4 1
## [39781] 4 5 5 2 4 5 2 2 3 4 1 2 1 2 5 1 2 5 2 1 2 3 2 5 1 5 1 4 4 5 5 5 3 3 1 1
## [39817] 5 4 2 2 4 4 4 2 5 4 4 3 4 1 3 3 3 5 5 1 1 1 4 1 4 3 1 5 1 3 4 1 2 5 3 5
## [39853] 3 3 5 2 1 1 2 4 3 5 4 4 1 2 2 4 2 5 1 5 5 3 4 4 4 4 5 1 3 4 4 5 2 3 5 2
## [39889] 1 1 5 5 4 2 5 2 5 2 1 3 5 3 5 1 5 2 4 2 2 2 4 4 3 2 5 5 5 2 1 3 2 5 2 2
## [39925] 1 3 1 2 2 2 2 5 4 1 3 5 5 2 3 4 5 4 5 4 5 2 1 1 5 3 2 2 3 5 2 4 5 5 1 3
## [39961] 3 3 3 2 4 1 4 5 5 4 1 3 1 2 3 2 5 1 5 5 1 3 5 2 4 4 4 3 1 4 2 4 1 1 5 2
## [39997] 4 2 3 3 4 1 1 1 2 3 3 4 1 1 1 1 2 1 1 1 4 5 1 3 3 2 5 3 3 4 4 5 5 4 1 5
## [40033] 4 4 3 1 4 4 3 5 1 5 4 1 3 1 5 3 2 1 3 4 2 1 2 1 1 5 5 2 3 3 3 3 5 3 4 5
## [40069] 5 1 1 1 2 4 5 3 5 1 2 1 1 5 4 3 4 2 4 2 1 1 1 1 4 4 1 4 5 2 3 1 1 5 3 5
## [40105] 4 3 2 1 1 2 1 4 3 2 2 3 5 1 4 1 3 5 5 1 2 2 4 3 3 4 2 4 4 3 3 2 4 2 1 1
## [40141] 2 2 2 5 4 5 2 5 4 5 1 2 1 4 5 1 2 5 4 3 3 1 5 4 1 2 5 4 3 5 3 5 1 4 4 4
## [40177] 2 2 2 1 3 2 5 3 5 1 2 5 4 2 2 5 5 5 1 1 3 5 2 1 1 1 3 4 1 5 4 4 2 2 5 2
## [40213] 4 1 3 1 3 5 1 2 5 2 3 2 2 5 4 3 4 3 4 4 4 3 5 5 1 5 2 1 3 2 3 2 2 5 1 4
## [40249] 2 1 4 2 4 1 2 3 2 1 2 4 3 3 2 3 1 4 3 2 4 1 2 3 5 2 2 3 3 3 4 3 3 1 5 3
## [40285] 5 1 4 4 5 2 5 1 1 1 3 4 2 2 4 3 2 4 5 4 2 2 5 2 5 3 1 2 3 4 2 3 4 4 2 4
## [40321] 2 3 1 3 1 4 4 2 5 4 1 3 2 1 3 3 2 5 4 5 4 3 5 1 4 4 4 1 1 2 1 5 4 2 2 1
## [40357] 2 4 2 5 4 2 2 3 5 3 2 4 3 3 4 1 5 4 1 2 5 3 4 1 5 4 2 5 1 4 4 4 5 3 4 3
## [40393] 4 4 1 5 5 5 4 4 2 5 5 3 5 2 2 2 1 4 4 1 5 5 2 3 5 2 1 4 1 5 5 3 4 5 2 5
## [40429] 1 5 5 5 2 5 4 5 5 2 4 1 4 1 1 5 1 1 1 4 5 4 4 4 3 3 1 4 2 2 2 1 3 1 5 2
## [40465] 2 4 4 2 1 5 4 2 4 2 2 4 3 1 4 3 5 2 3 3 3 4 2 4 2 3 3 1 2 2 3 4 2 3 1 3
## [40501] 3 5 5 2 2 4 1 1 3 4 4 1 3 3 3 2 1 5 2 2 5 3 4 3 3 2 5 4 1 1 3 4 4 2 5 1
## [40537] 1 5 1 1 2 5 2 1 1 2 1 5 3 4 3 2 4 2 5 4 2 3 2 2 3 4 2 3 5 5 5 1 4 4 5 5
## [40573] 1 3 3 1 4 4 4 1 3 2 2 3 3 1 2 5 5 1 3 3 1 4 3 4 2 5 5 5 2 2 3 3 2 4 4 1
## [40609] 1 2 3 1 4 4 4 4 2 4 4 5 3 3 4 2 1 5 2 3 1 1 2 5 1 4 1 3 1 1 3 4 3 5 1 4
## [40645] 4 4 3 3 4 3 3 1 5 1 5 4 1 2 4 4 4 2 5 3 3 1 4 5 4 5 3 5 1 2 3 5 3 3 5 4
## [40681] 4 3 2 1 3 3 5 1 5 5 1 3 4 3 4 1 2 4 4 3 4 5 1 5 2 1 3 2 1 4 4 5 2 4 1 2
## [40717] 2 4 3 2 3 1 2 2 4 2 5 3 4 4 4 5 4 2 2 4 1 1 4 4 4 1 1 1 3 5 3 3 2 2 5 3
## [40753] 5 1 3 4 2 2 1 5 3 1 5 2 1 2 3 4 1 4 3 3 3 2 4 5 5 4 2 3 4 4 5 3 3 2 3 2
## [40789] 2 5 3 2 3 4 4 1 1 2 5 4 1 2 1 1 3 4 5 4 3 3 1 4 3 1 4 2 4 3 5 5 4 4 1 3
## [40825] 2 3 2 2 4 2 4 2 5 2 3 5 4 4 2 3 4 5 3 3 2 3 4 4 1 1 1 2 5 4 3 2 5 5 1 4
## [40861] 3 5 2 5 2 2 5 1 5 2 3 1 3 2 3 5 3 4 5 5 4 1 4 5 2 4 3 2 3 1 4 2 5 5 4 2
## [40897] 2 1 3 1 4 5 5 4 2 2 2 1 1 5 2 1 4 4 4 1 3 4 3 3 4 1 1 4 4 3 1 1 5 1 3 4
## [40933] 1 1 3 4 3 1 4 1 4 2 3 2 2 3 1 4 1 4 4 5 3 1 2 3 3 3 2 4 2 5 3 5 2 5 4 4
## [40969] 5 5 5 4 3 1 2 4 5 3 3 3 3 1 3 5 4 2 3 1 2 4 3 5 1 4 3 2 2 3 4 1 5 3 1 1
## [41005] 3 2 4 5 4 3 2 2 1 2 3 3 3 4 3 2 1 2 1 1 2 4 2 1 1 5 3 5 1 3 5 3 2 3 4 4
## [41041] 2 4 5 1 5 5 1 5 3 4 2 1 1 1 5 4 4 4 1 5 5 2 1 5 2 2 4 3 5 1 3 3 3 3 1 4
## [41077] 5 3 4 3 4 4 5 2 4 5 4 4 5 2 5 5 3 1 1 3 3 2 4 3 5 2 4 1 4 5 5 5 5 3 1 4
## [41113] 3 3 5 2 1 3 1 3 1 5 2 5 5 5 4 5 2 5 2 4 1 1 3 3 2 4 1 3 2 2 5 5 4 1 5 5
## [41149] 3 5 1 1 4 1 1 1 2 5 2 5 1 2 5 3 5 2 1 4 5 2 5 2 4 5 2 5 3 5 1 5 4 1 4 5
## [41185] 1 5 4 3 5 4 5 1 4 4 2 5 1 2 1 4 3 2 1 1 3 5 5 3 3 4 3 2 5 5 4 1 3 1 3 2
## [41221] 5 4 5 5 2 4 4 2 2 2 4 2 3 3 1 5 3 2 1 5 5 2 3 5 4 2 4 3 2 3 3 4 4 2 3 3
## [41257] 3 3 5 5 5 2 4 4 4 2 5 5 4 1 2 4 1 1 3 2 4 3 3 2 3 2 1 3 1 2 5 2 5 2 2 4
## [41293] 2 2 5 4 5 2 1 5 5 2 3 4 5 2 4 4 5 5 5 1 4 2 3 1 3 4 3 5 5 5 2 5 5 4 4 5
## [41329] 5 1 5 5 5 4 3 2 4 5 2 1 1 5 3 4 1 2 4 2 2 3 1 3 4 1 2 1 4 1 4 1 1 1 5 5
## [41365] 4 1 5 1 2 2 4 2 1 3 3 3 1 3 1 4 1 2 4 3 1 1 5 4 5 4 1 5 1 5 4 2 4 2 5 5
## [41401] 3 3 1 5 3 5 1 2 1 1 2 3 4 3 1 3 2 2 2 5 1 2 1 2 4 4 4 3 2 5 3 1 4 5 2 4
## [41437] 4 3 4 3 5 3 4 2 3 2 5 4 2 2 1 1 3 1 4 5 5 2 5 2 2 1 4 4 4 1 4 3 4 3 3 1
## [41473] 3 3 1 1 2 5 3 3 4 5 4 2 3 1 5 2 3 3 4 3 2 5 3 3 2 3 5 2 5 2 1 1 5 2 5 2
## [41509] 2 3 2 5 3 4 4 2 3 3 5 5 1 4 1 3 4 5 2 5 1 5 2 5 3 2 1 4 5 3 3 3 1 5 3 3
## [41545] 1 3 3 2 5 2 5 4 3 2 2 5 1 2 3 2 3 3 4 2 2 1 5 3 4 3 2 2 1 4 2 5 1 2 1 5
## [41581] 3 4 1 3 2 2 2 3 1 4 2 1 4 2 1 5 4 1 3 1 2 4 4 2 4 5 5 4 4 5 1 3 3 5 3 2
## [41617] 1 1 1 5 4 1 5 2 3 4 5 4 1 5 5 1 3 3 3 4 1 5 5 2 3 2 5 5 5 2 3 3 3 1 3 4
## [41653] 1 4 3 5 3 5 1 1 3 5 1 3 1 2 1 2 1 3 3 4 5 3 3 1 4 2 4 2 4 2 3 5 1 1 1 5
## [41689] 1 1 3 3 2 2 2 5 3 2 2 4 1 4 5 1 4 2 2 1 4 3 2 5 5 2 1 1 3 5 2 4 4 2 4 3
## [41725] 4 5 5 5 2 2 2 4 2 3 2 1 2 4 1 3 5 1 4 3 1 3 5 1 5 3 1 3 5 4 3 3 2 2 3 3
## [41761] 5 5 1 2 4 2 1 5 2 3 2 2 2 2 5 4 1 2 2 3 1 5 1 2 2 1 1 1 4 2 4 3 1 4 3 1
## [41797] 5 3 3 3 1 5 5 5 5 2 1 5 3 1 2 5 2 4 4 2 4 3 2 5 5 5 1 1 5 1 5 5 5 4 4 3
## [41833] 4 4 4 1 2 5 4 2 4 1 4 4 3 1 4 5 4 2 5 5 5 2 2 4 1 5 5 3 2 3 1 5 2 3 4 2
## [41869] 3 3 2 1 1 4 3 5 2 1 2 2 1 3 5 5 5 4 5 2 3 2 3 2 4 1 5 2 2 3 5 2 3 2 1 4
## [41905] 2 1 3 4 4 4 1 4 5 3 4 1 5 4 3 5 1 2 4 4 5 5 3 4 2 5 2 3 3 5 1 4 4 3 5 4
## [41941] 5 1 4 3 1 5 1 5 4 3 5 3 4 5 4 1 2 5 2 5 5 4 1 5 1 4 3 5 3 3 1 5 4 4 1 4
## [41977] 4 5 1 4 1 2 3 4 5 3 2 3 1 2 1 5 3 5 3 3 3 1 4 4 5 3 4 5 5 3 3 4 4 4 5 5
## [42013] 4 3 2 2 4 3 2 1 1 5 3 1 3 4 1 5 5 3 1 5 5 5 1 2 3 1 1 1 5 2 3 4 4 5 5 2
## [42049] 1 4 3 5 4 5 4 4 1 3 1 2 2 3 1 2 5 1 4 1 1 5 1 4 5 5 4 5 4 5 4 2 2 5 1 4
## [42085] 1 5 3 4 4 5 4 2 4 2 3 2 2 5 4 2 3 1 4 1 3 5 5 4 2 3 5 5 5 2 5 5 2 2 1 3
## [42121] 5 3 2 1 2 3 4 5 5 4 3 1 3 3 2 3 3 5 2 1 5 3 5 1 2 3 3 2 2 1 2 2 3 3 1 5
## [42157] 3 3 2 3 3 4 4 4 3 1 1 2 1 5 1 1 5 1 3 1 1 2 5 5 3 2 5 2 1 4 1 5 3 5 3 1
## [42193] 5 2 2 4 5 5 5 3 1 5 3 4 5 3 3 5 2 2 4 4 4 4 3 3 2 4 2 4 5 2 3 5 3 3 1 2
## [42229] 1 1 4 2 5 2 5 5 4 2 2 4 3 4 2 4 5 4 2 2 4 3 3 5 4 4 3 3 2 2 3 2 1 3 3 5
## [42265] 3 4 3 5 1 2 5 3 3 3 2 2 1 4 4 4 3 4 4 1 2 3 3 4 4 5 2 4 3 4 2 1 4 4 3 4
## [42301] 1 1 3 5 4 1 1 1 2 5 4 5 2 4 5 3 1 2 2 1 5 3 4 1 4 2 2 4 3 5 3 1 1 2 3 3
## [42337] 2 5 3 2 2 1 5 2 1 1 1 3 3 2 4 2 2 3 4 2 2 2 1 4 5 5 4 5 3 2 2 4 2 4 5 2
## [42373] 1 3 3 2 5 5 5 5 2 5 1 2 1 1 1 1 3 2 2 5 2 5 5 3 5 3 2 3 1 2 3 3 2 3 2 4
## [42409] 1 2 1 3 3 4 3 2 2 1 4 1 4 1 5 5 5 1 4 4 4 2 1 4 1 3 3 4 1 5 2 2 3 1 3 3
## [42445] 4 2 5 5 1 3 1 1 1 4 4 1 2 5 3 5 4 2 5 5 1 1 1 2 1 3 1 5 4 4 3 1 1 1 4 3
## [42481] 1 5 4 3 2 3 2 2 4 5 1 4 4 2 3 5 2 1 1 1 2 5 2 1 1 1 4 5 1 2 3 4 4 5 1 3
## [42517] 3 4 2 2 3 4 4 2 4 3 3 5 1 4 1 4 4 1 5 5 4 3 2 5 5 3 1 5 3 3 5 1 5 1 1 3
## [42553] 1 4 3 3 2 1 3 2 4 4 5 3 1 5 2 3 3 1 2 3 5 4 2 2 1 4 5 1 5 3 1 3 4 4 4 4
## [42589] 3 1 4 2 2 5 5 3 3 5 2 2 2 3 1 3 5 1 2 4 3 1 1 3 5 2 3 3 5 3 2 3 2 2 5 5
## [42625] 4 5 1 2 2 5 2 3 1 5 5 1 4 3 5 5 5 5 4 2 1 1 2 1 5 2 4 5 4 3 1 4 3 4 1 1
## [42661] 2 1 1 3 1 3 2 5 4 5 4 5 2 3 1 5 1 1 5 5 3 5 4 4 1 4 1 1 4 5 3 5 4 5 4 4
## [42697] 1 2 3 1 4 2 1 2 5 1 1 1 3 3 5 5 4 2 4 4 2 1 2 4 2 1 1 5 1 4 5 4 4 1 3 1
## [42733] 3 4 3 5 5 1 5 4 3 4 1 1 5 5 5 2 5 2 4 3 3 3 5 2 5 1 4 2 1 3 2 5 3 2 4 5
## [42769] 2 2 1 4 2 5 1 1 5 3 4 5 1 3 3 4 2 2 2 5 3 1 2 3 3 1 5 4 4 5 1 3 1 2 2 2
## [42805] 4 5 5 3 2 5 1 3 2 2 2 1 1 4 4 1 5 4 4 5 2 4 3 4 4 2 4 1 5 2 5 5 1 2 3 1
## [42841] 1 1 1 3 4 2 2 1 2 4 2 2 3 1 4 2 5 5 1 2 2 3 5 1 2 5 3 2 5 4 5 1 3 4 1 4
## [42877] 1 5 2 3 1 4 2 2 1 4 4 1 2 4 3 3 5 1 3 5 3 1 1 5 2 5 2 1 5 4 5 2 4 4 3 3
## [42913] 2 3 4 5 5 5 3 2 5 5 3 2 1 5 1 5 5 1 2 5 2 3 4 1 1 2 1 1 1 1 5 2 4 4 4 2
## [42949] 5 5 5 4 5 1 5 1 2 5 4 5 1 2 5 5 3 5 4 2 4 2 4 2 1 3 3 4 5 4 4 2 3 5 1 5
## [42985] 3 3 2 4 4 1 4 5 5 3 1 1 5 3 4 3 3 1 1 2 5 3 4 2 3 1 1 4 2 3 1 4 1 2 2 4
## [43021] 4 4 4 1 3 4 4 5 5 4 5 3 4 2 1 4 3 4 2 2 5 5 4 2 5 2 1 5 2 2 4 4 1 4 5 4
## [43057] 2 2 2 3 2 2 1 1 2 4 4 3 5 2 5 4 1 4 3 3 5 2 4 4 4 5 4 3 3 2 2 2 2 1 1 1
## [43093] 3 4 4 1 1 3 4 4 3 2 3 5 1 5 5 2 2 2 1 2 1 1 2 3 3 1 3 3 1 3 1 5 2 3 2 2
## [43129] 1 3 1 5 2 2 2 4 4 5 2 5 5 4 1 4 3 5 1 2 3 4 3 5 1 5 4 1 2 5 4 5 5 3 5 1
## [43165] 5 3 1 4 3 4 4 5 2 2 5 2 5 1 3 1 2 5 3 5 3 5 5 3 3 2 1 3 4 5 5 3 1 5 3 4
## [43201] 2 3 1 1 2 5 4 2 3 4 1 2 5 5 2 4 5 3 2 4 1 3 5 2 3 2 2 3 2 3 5 5 1 5 4 4
## [43237] 4 1 4 2 3 3 3 3 4 3 4 1 3 5 3 3 3 1 3 4 2 4 5 3 1 3 5 3 3 2 1 2 3 1 1 5
## [43273] 2 4 1 4 4 1 2 1 5 3 3 5 5 4 1 2 1 4 5 1 2 1 1 5 5 3 3 5 4 1 2 4 1 4 2 4
## [43309] 3 5 2 4 5 2 1 4 5 4 2 3 4 5 5 5 3 1 3 4 3 3 3 4 4 4 1 5 4 5 4 2 5 2 5 5
## [43345] 1 1 4 2 5 4 3 2 5 2 4 2 4 5 5 2 3 3 1 3 4 3 2 2 1 1 4 3 3 4 3 2 5 1 4 5
## [43381] 1 2 4 3 4 4 4 3 2 2 5 1 1 4 5 1 4 5 4 4 1 5 3 4 5 1 1 4 4 3 2 3 4 1 1 5
## [43417] 1 4 3 2 4 5 3 3 5 5 2 1 3 4 5 1 3 1 2 1 2 4 1 1 2 1 1 3 5 1 2 5 5 4 4 3
## [43453] 1 5 5 3 3 3 3 2 2 3 3 4 2 1 5 1 4 2 4 2 3 2 3 2 3 4 1 5 5 5 5 3 5 3 2 4
## [43489] 5 4 4 3 2 3 2 3 3 2 5 3 1 3 5 4 4 5 3 4 1 3 3 2 2 2 2 1 1 5 2 4 1 2 5 3
## [43525] 3 4 3 1 1 2 1 4 3 2 2 2 4 1 3 2 1 3 5 3 4 2 4 5 1 1 1 1 1 1 4 4 5 3 5 2
## [43561] 3 5 4 3 3 5 4 5 4 4 4 5 1 5 1 2 1 3 5 5 2 4 1 1 3 1 1 2 5 4 1 1 4 4 5 1
## [43597] 3 5 1 4 4 1 1 5 2 2 2 4 1 1 5 3 5 2 1 1 5 5 2 4 1 2 3 2 4 4 2 4 1 2 2 3
## [43633] 5 1 3 3 4 3 3 2 4 4 2 2 4 1 5 1 1 1 5 3 1 3 4 5 4 3 2 4 3 1 3 2 4 3 1 5
## [43669] 3 3 5 5 5 5 5 5 2 3 2 3 5 2 3 5 5 3 2 5 5 4 1 5 5 1 5 5 3 5 5 4 2 4 2 3
## [43705] 3 1 3 2 2 1 5 5 1 3 2 4 4 3 2 3 1 5 4 1 3 2 3 4 1 4 1 3 4 4 5 4 3 3 2 3
## [43741] 4 5 3 3 1 4 2 1 3 4 1 5 2 4 1 3 2 2 2 1 3 4 3 2 3 5 1 1 3 3 3 5 2 5 4 2
## [43777] 4 5 4 5 3 3 3 2 2 4 2 5 5 5 2 4 3 4 5 2 3 5 4 4 4 3 1 3 5 5 3 2 3 2 4 1
## [43813] 3 5 1 4 4 5 4 2 3 5 3 5 4 3 4 1 3 1 1 4 1 4 2 4 1 2 5 2 1 4 3 4 2 5 5 2
## [43849] 4 1 2 1 3 1 2 3 1 5 5 4 2 5 5 2 5 3 5 2 1 1 5 1 2 2 3 1 4 2 3 3 3 5 5 5
## [43885] 4 5 1 5 1 3 2 5 1 4 1 2 3 1 4 5 3 4 5 3 2 1 5 2 1 5 3 3 5 5 5 1 3 5 4 1
## [43921] 1 3 2 1 3 5 1 5 2 1 2 2 2 4 2 5 3 1 5 4 2 1 1 5 1 1 4 5 3 1 2 1 5 5 5 3
## [43957] 5 3 2 1 5 3 4 2 4 3 5 5 4 4 4 2 3 5 5 4 1 1 5 3 2 5 4 2 5 4 1 2 3 3 5 4
## [43993] 2 1 5 4 4 5 5 1 1 3 1 3 1 3 3 2 5 3 5 4 4 3 2 2 4 5 2 3 2 3 2 3 1 1 3 3
## [44029] 4 5 1 4 3 2 1 1 5 4 4 3 1 1 4 4 2 5 2 5 2 4 3 5 2 3 3 3 3 3 3 4 2 3 3 5
## [44065] 2 1 2 3 4 4 5 5 2 5 1 3 3 4 5 3 1 4 5 3 3 5 4 5 3 3 5 2 5 5 2 4 1 3 3 4
## [44101] 5 5 2 4 2 5 2 5 5 5 3 4 2 5 3 1 1 1 3 2 3 2 4 1 2 5 2 1 4 3 5 3 4 5 1 3
## [44137] 5 5 5 4 5 5 1 3 5 3 1 2 3 5 5 1 2 1 1 2 4 5 4 4 3 5 2 4 4 1 1 5 3 3 4 4
## [44173] 2 2 1 3 1 3 4 4 4 2 3 5 2 3 2 4 4 3 5 2 1 3 5 1 5 1 3 5 5 1 5 4 3 4 2 3
## [44209] 4 5 2 4 4 2 2 3 2 4 2 3 5 2 1 5 1 4 2 5 1 5 2 4 5 4 4 3 5 5 3 4 1 5 3 4
## [44245] 3 5 2 2 3 2 4 3 3 2 1 3 1 1 5 1 5 5 5 1 1 3 2 2 3 1 1 5 5 1 5 5 1 3 4 4
## [44281] 5 1 3 5 5 5 4 3 5 5 1 4 5 4 3 2 1 5 3 2 1 1 5 1 5 2 5 1 2 4 3 4 4 5 1 4
## [44317] 2 1 4 3 3 3 2 2 2 5 3 3 5 5 1 5 1 5 2 5 1 5 4 4 4 1 2 1 2 2 3 4 4 4 4 1
## [44353] 2 1 1 1 1 2 4 5 2 3 3 1 3 2 2 5 3 4 2 2 4 2 3 1 2 2 1 4 4 3 2 1 5 5 1 2
## [44389] 3 1 2 5 1 3 2 2 2 2 5 2 4 4 1 2 2 4 2 3 3 3 1 5 2 4 3 2 3 5 4 1 1 3 4 5
## [44425] 5 2 1 3 5 4 3 1 5 3 4 3 4 2 2 3 2 5 1 2 1 5 3 4 3 3 5 1 5 4 4 3 5 1 3 3
## [44461] 2 5 2 1 5 2 4 2 3 4 1 1 5 2 2 1 1 3 2 2 4 1 5 2 4 5 1 5 5 5 2 1 2 4 4 5
## [44497] 4 2 5 4 2 4 2 4 2 1 2 3 4 5 3 3 5 1 4 3 4 1 4 3 4 4 3 1 2 2 3 5 4 5 5 4
## [44533] 2 5 1 3 2 2 3 5 2 4 2 3 4 5 5 1 1 2 1 1 2 4 2 4 2 5 3 5 4 4 1 1 4 2 3 3
## [44569] 4 3 5 4 4 2 2 5 2 2 5 1 3 2 5 1 2 4 1 3 1 3 2 5 3 5 2 4 3 1 1 5 5 3 1 1
## [44605] 3 1 5 5 5 5 4 1 5 3 2 3 3 2 2 4 5 3 2 5 1 4 2 4 3 4 4 4 2 5 3 1 5 1 5 1
## [44641] 2 3 3 4 5 4 2 5 1 3 4 3 5 2 5 3 1 5 2 2 2 2 1 3 2 1 4 2 2 4 4 3 1 1 5 2
## [44677] 1 5 5 4 3 5 2 2 4 2 3 1 1 1 1 3 2 3 5 1 1 1 1 3 3 3 3 3 1 4 3 1 2 2 3 5
## [44713] 3 4 2 3 2 2 1 4 2 2 1 3 1 4 4 2 1 1 2 2 3 3 3 2 2 5 3 4 1 1 1 1 2 4 2 4
## [44749] 2 5 1 3 5 1 2 5 5 5 2 4 4 4 2 4 2 5 5 1 3 1 4 3 3 3 1 5 3 5 3 1 4 1 4 5
## [44785] 5 4 4 1 2 1 3 2 4 5 3 2 4 5 4 2 1 1 4 1 5 1 5 2 1 5 4 1 4 2 1 1 1 2 3 2
## [44821] 4 3 5 5 5 5 3 2 1 2 3 3 1 2 4 4 2 3 5 1 2 3 4 2 4 5 3 5 5 2 5 2 4 4 3 4
## [44857] 5 4 2 1 5 5 1 2 4 3 5 2 1 1 2 1 3 4 4 1 4 3 3 3 4 2 5 3 5 1 1 5 3 2 3 3
## [44893] 3 1 5 5 1 3 4 1 4 3 2 3 1 3 3 3 3 5 4 4 4 5 1 3 3 5 5 5 5 1 3 3 1 3 5 5
## [44929] 1 1 1 2 4 3 4 5 5 3 3 4 2 2 4 5 1 2 3 1 5 3 2 2 2 5 3 5 4 3 4 4 2 3 2 1
## [44965] 3 3 1 5 2 5 1 4 4 2 2 5 5 2 3 3 5 4 3 2 4 5 2 4 1 1 4 1 3 4 2 1 5 5 1 3
## [45001] 2 1 5 4 4 1 4 1 5 1 2 4 3 3 2 2 4 2 2 4 2 3 1 4 5 2 3 5 2 4 2 4 1 1 2 1
## [45037] 3 2 5 2 4 4 5 5 2 1 2 3 3 5 3 1 3 4 2 5 3 2 4 2 3 5 2 1 5 2 5 3 2 4 2 4
## [45073] 5 1 1 3 3 1 2 4 1 2 3 1 3 4 2 4 2 5 4 4 2 2 2 4 2 1 4 3 4 5 3 2 3 4 3 3
## [45109] 2 3 1 2 5 3 1 2 4 1 5 3 1 5 3 1 3 2 5 2 1 3 1 5 3 4 4 5 1 5 4 1 5 5 1 4
## [45145] 3 2 4 5 4 4 5 3 4 4 4 5 1 4 5 2 2 5 4 2 1 2 5 5 1 1 5 1 5 3 4 4 5 1 3 4
## [45181] 4 2 3 2 4 5 4 3 2 4 5 4 5 4 5 1 1 4 5 1 2 5 2 3 4 1 5 5 2 2 2 2 3 2 3 3
## [45217] 4 5 1 4 1 5 5 1 1 1 3 1 2 5 4 2 4 1 4 4 3 5 2 4 1 4 1 4 3 4 5 1 2 3 5 5
## [45253] 4 3 2 1 2 3 4 3 2 4 2 3 4 3 5 3 3 1 1 3 3 5 5 5 2 2 5 2 5 2 1 5 3 4 4 4
## [45289] 2 5 4 2 1 5 1 2 5 2 4 5 5 2 5 1 1 3 2 3 1 1 1 1 2 5 2 5 1 1 1 1 2 4 5 2
## [45325] 2 5 5 1 2 4 1 5 2 3 3 5 2 5 3 4 4 1 2 5 3 4 2 4 2 2 1 2 5 4 3 2 5 2 2 3
## [45361] 1 5 3 3 4 1 4 3 5 2 2 4 4 3 4 3 3 2 4 5 1 3 3 1 2 2 2 1 5 4 5 2 4 4 3 4
## [45397] 1 2 4 2 1 1 5 3 2 3 2 1 4 2 4 4 1 5 4 3 2 4 1 5 2 3 2 4 5 3 5 5 4 3 1 5
## [45433] 2 2 1 3 4 4 4 3 2 3 2 1 1 2 1 2 5 1 1 2 3 3 5 1 2 4 4 3 4 2 2 5 2 2 5 4
## [45469] 1 2 3 5 1 4 5 5 4 3 4 2 5 5 3 3 2 2 2 2 5 2 1 3 1 3 2 4 3 1 1 1 2 3 2 5
## [45505] 2 2 4 3 3 5 2 4 5 1 3 1 4 2 5 3 2 2 3 1 3 2 2 3 4 1 3 1 4 2 4 1 5 4 4 5
## [45541] 4 5 1 3 2 5 3 2 3 2 2 1 1 2 1 3 5 2 5 5 2 4 4 2 2 3 1 5 4 2 4 4 3 1 2 4
## [45577] 4 2 1 3 5 2 5 5 5 5 5 5 3 5 5 1 3 1 1 2 5 2 2 5 5 4 1 4 2 3 3 5 5 2 5 1
## [45613] 2 3 2 1 4 1 5 1 5 5 2 2 3 2 5 5 1 2 5 3 1 4 1 5 3 3 2 3 1 3 4 1 5 4 4 2
## [45649] 3 4 4 4 1 5 2 5 3 4 5 4 4 1 3 5 3 3 1 2 1 1 3 4 3 1 3 5 5 5 3 3 2 1 3 4
## [45685] 2 3 5 3 4 2 3 3 1 3 3 2 3 4 3 3 5 1 2 4 5 4 3 3 4 3 4 1 1 3 4 5 1 1 1 5
## [45721] 4 5 3 4 2 4 4 4 5 5 5 4 4 1 5 2 3 1 1 4 2 1 2 1 4 3 2 5 1 1 3 5 3 3 4 3
## [45757] 4 5 1 2 1 4 5 2 4 3 5 4 5 2 5 5 4 4 2 4 2 2 2 3 4 5 1 1 2 5 4 5 2 4 1 1
## [45793] 1 3 4 5 3 2 4 1 1 3 3 5 2 2 2 3 5 1 4 3 1 5 1 3 1 4 2 4 2 1 4 5 3 4 2 4
## [45829] 1 5 1 4 1 1 3 4 4 1 2 2 1 2 2 2 5 2 1 2 2 5 2 5 1 5 1 4 4 3 4 2 5 4 3 5
## [45865] 2 4 1 4 3 3 4 4 3 5 3 1 4 2 1 3 4 4 1 5 3 2 1 3 4 2 2 2 5 3 4 3 2 3 2 2
## [45901] 3 4 1 2 2 3 4 3 3 5 2 2 4 1 5 4 5 1 5 2 3 4 4 5 1 1 3 4 3 2 4 2 3 3 2 2
## [45937] 5 2 1 4 5 1 4 5 4 1 4 2 5 3 5 1 2 4 3 5 2 4 5 4 4 3 2 3 5 5 1 1 1 5 5 2
## [45973] 4 4 5 4 2 1 5 3 1 5 2 4 1 1 1 2 3 5 2 3 1 1 4 3 3 1 5 2 3 3 5 2 5 4 4 1
## [46009] 1 5 2 5 1 5 2 3 4 1 4 1 3 1 3 1 4 1 2 2 2 4 1 5 5 1 4 3 2 4 2 4 2 2 1 2
## [46045] 4 3 2 4 3 1 3 5 1 1 3 4 5 1 3 5 1 1 4 3 3 1 2 4 1 1 2 2 1 1 5 1 2 5 5 2
## [46081] 3 2 2 4 3 1 5 1 1 4 3 1 2 4 5 5 3 4 5 4 2 1 4 4 3 3 4 3 3 1 5 1 5 3 2 4
## [46117] 3 2 5 1 3 1 3 2 3 4 5 4 1 2 4 4 5 2 1 1 2 4 5 3 3 4 1 4 4 4 3 1 5 4 1 4
## [46153] 3 4 2 2 3 4 3 2 5 3 4 4 1 3 1 2 3 1 1 4 3 5 1 4 3 4 4 4 4 4 3 1 3 1 4 1
## [46189] 3 5 2 5 2 1 4 5 5 3 2 3 2 3 1 2 5 4 5 3 1 4 1 3 4 1 5 2 3 2 3 5 4 3 1 5
## [46225] 3 5 4 2 3 3 3 1 4 3 3 2 2 5 1 5 5 5 2 2 5 4 3 5 1 1 2 1 2 2 3 2 5 2 2 2
## [46261] 2 1 2 4 4 3 1 2 5 5 1 5 2 5 1 5 1 2 1 2 4 1 2 3 5 1 3 3 3 2 3 5 4 4 5 4
## [46297] 1 5 5 1 2 3 1 3 3 2 5 1 5 3 5 4 5 1 2 5 2 5 2 3 1 2 3 2 1 5 1 5 3 5 2 5
## [46333] 5 2 1 2 2 1 1 4 3 4 4 5 5 2 4 1 1 3 4 4 3 2 5 1 4 1 4 4 4 4 3 5 5 5 4 4
## [46369] 1 4 2 2 1 1 3 5 5 5 4 2 3 3 4 5 3 4 4 1 1 5 5 3 2 1 1 2 1 4 3 4 3 1 2 4
## [46405] 2 4 2 5 2 3 2 1 3 3 2 3 5 5 3 4 3 3 5 3 4 2 5 5 2 4 5 2 4 3 4 4 2 1 4 3
## [46441] 4 2 5 4 4 4 1 4 4 4 5 2 2 3 4 3 2 3 1 4 3 2 4 1 1 3 5 5 3 2 4 2 4 2 1 5
## [46477] 1 4 5 4 1 1 2 5 5 5 5 1 4 1 5 2 2 4 5 5 5 1 5 2 4 4 1 3 2 5 2 3 2 5 5 4
## [46513] 3 5 5 1 2 3 3 4 2 1 2 5 4 4 3 5 4 5 5 2 5 1 1 4 3 2 4 4 5 2 4 5 1 1 5 4
## [46549] 5 3 4 4 1 3 2 5 3 4 2 3 5 3 1 1 2 3 4 3 5 2 3 3 1 5 4 4 2 4 4 1 5 5 1 1
## [46585] 3 5 4 2 3 5 4 5 1 3 4 3 5 2 3 2 1 2 1 2 2 5 2 4 4 4 1 3 1 4 3 3 2 5 3 1
## [46621] 4 4 4 4 3 4 1 5 5 4 1 5 3 5 1 2 1 3 4 4 2 4 1 5 3 2 4 2 5 5 1 3 5 5 2 4
## [46657] 2 2 5 2 2 3 3 4 2 2 2 3 1 2 4 2 5 2 5 4 1 1 5 5 5 2 1 2 1 1 4 3 4 3 4 3
## [46693] 4 1 5 3 1 5 2 1 2 5 5 4 2 4 3 3 5 3 2 3 1 4 5 1 3 1 3 2 4 2 1 1 5 2 4 5
## [46729] 4 1 4 2 1 2 3 3 3 4 4 2 3 3 5 5 3 3 2 3 3 1 2 1 1 5 3 4 1 5 2 5 5 4 3 4
## [46765] 1 4 4 3 5 1 1 2 1 3 4 3 2 1 3 4 1 1 4 2 5 3 5 2 1 1 2 2 1 2 5 1 1 3 4 5
## [46801] 2 4 4 5 3 5 2 2 2 1 5 4 4 5 5 4 5 1 5 1 5 2 5 2 1 5 2 2 2 5 4 3 3 5 3 4
## [46837] 4 3 4 2 4 2 2 3 2 3 2 3 1 4 1 2 5 2 4 3 2 3 4 1 1 2 4 1 3 5 2 5 4 1 5 2
## [46873] 4 1 1 4 1 5 5 5 5 5 2 2 5 1 5 2 4 3 4 4 3 2 3 1 5 3 2 5 5 1 5 3 5 1 4 3
## [46909] 2 4 3 2 5 2 4 1 2 4 1 1 4 4 5 4 3 5 3 5 5 5 3 2 1 4 4 2 5 3 3 5 4 2 5 3
## [46945] 4 3 2 1 4 1 5 5 2 3 4 3 1 3 3 3 5 5 4 1 2 1 1 2 1 3 4 3 3 2 1 5 3 2 4 3
## [46981] 5 3 1 2 2 1 4 4 5 2 1 5 4 1 3 4 5 1 4 4 4 5 2 5 4 3 1 5 3 5 4 4 1 3 3 4
## [47017] 4 4 5 4 1 5 3 1 5 1 1 4 3 4 2 4 3 2 5 2 1 1 1 5 1 1 1 2 1 5 1 2 1 1 3 4
## [47053] 2 4 3 4 5 5 3 3 5 4 2 5 3 5 1 5 4 2 3 4 4 3 5 2 4 1 5 3 4 4 3 2 1 5 2 2
## [47089] 4 1 4 3 4 4 5 3 2 1 2 1 1 4 1 2 5 1 3 1 4 5 5 3 2 1 1 5 4 3 4 5 3 2 3 5
## [47125] 1 1 2 5 2 1 4 3 1 1 3 5 2 2 1 5 4 4 2 1 3 4 1 5 2 3 1 4 3 2 5 5 4 4 5 1
## [47161] 5 1 1 2 1 2 4 4 4 3 3 5 1 4 5 4 1 4 4 3 3 1 2 2 2 2 1 3 1 5 5 4 2 3 2 1
## [47197] 1 1 2 4 2 5 1 4 3 2 2 4 3 3 3 2 4 2 4 5 5 1 4 5 2 2 3 4 4 2 3 3 2 5 3 2
## [47233] 2 5 5 2 5 2 1 3 2 4 1 5 2 1 2 5 3 4 2 1 4 5 4 3 5 4 2 4 3 2 3 1 2 3 5 4
## [47269] 3 5 2 2 5 2 5 2 4 3 2 4 1 4 3 2 4 2 4 2 2 2 1 5 5 3 1 3 2 5 1 5 2 3 2 4
## [47305] 4 3 3 5 3 1 4 5 5 3 3 1 2 4 3 1 2 2 2 1 3 2 4 3 2 4 2 2 4 4 3 5 5 1 4 1
## [47341] 2 2 1 2 5 2 2 3 3 5 1 3 5 5 2 1 5 1 1 1 5 2 4 1 2 1 2 1 1 1 4 4 2 3 3 1
## [47377] 1 4 3 2 3 4 5 5 2 3 1 1 1 5 1 4 5 1 4 5 5 3 4 5 2 4 5 1 4 5 3 4 2 2 4 4
## [47413] 3 5 5 4 3 5 2 2 5 2 2 4 5 5 4 5 5 5 2 4 2 5 2 3 2 3 5 3 2 3 5 3 5 3 4 5
## [47449] 3 5 2 5 4 5 3 4 1 5 1 2 2 5 4 1 3 1 1 3 1 1 5 4 5 3 5 5 1 4 5 1 3 5 1 5
## [47485] 3 1 1 1 1 1 3 5 1 2 5 4 5 1 4 5 1 5 3 1 4 2 1 2 4 4 2 3 1 3 5 1 2 2 3 4
## [47521] 3 4 1 4 3 1 4 3 2 5 4 4 3 4 3 1 5 1 3 2 5 4 4 2 3 4 4 2 4 2 3 1 2 1 3 5
## [47557] 3 5 4 2 4 1 2 2 1 1 2 2 4 4 1 4 1 2 4 5 4 4 1 2 1 3 1 1 5 5 2 4 1 3 4 5
## [47593] 2 2 2 1 5 4 2 3 4 4 1 4 4 5 4 5 4 3 3 1 4 2 2 2 4 3 2 3 5 2 4 4 2 3 3 2
## [47629] 3 2 2 4 4 4 3 2 2 1 2 3 1 2 1 4 3 2 4 2 2 2 5 3 1 1 4 3 4 1 1 3 1 1 3 3
## [47665] 1 4 3 2 2 4 4 2 5 5 1 2 4 3 3 1 1 2 1 3 3 4 3 4 5 3 1 5 4 3 2 2 2 3 4 1
## [47701] 3 1 3 1 3 5 1 5 1 1 5 1 3 1 3 5 4 1 5 5 3 5 1 1 3 5 5 3 2 1 2 2 2 4 2 2
## [47737] 1 3 4 2 3 5 4 1 1 1 2 1 2 4 1 2 2 5 2 1 1 2 4 2 1 2 1 2 2 5 1 5 1 1 1 3
## [47773] 4 2 1 3 2 3 5 4 4 1 1 3 4 1 3 5 1 2 5 2 3 5 1 5 4 1 2 3 4 5 3 4 4 5 1 1
## [47809] 2 4 3 2 5 1 4 1 1 4 3 2 5 3 4 5 2 5 3 5 5 1 4 2 1 4 1 3 2 4 3 1 5 2 3 3
## [47845] 5 2 5 5 1 3 1 2 1 4 4 5 4 3 3 5 3 5 4 5 2 4 4 2 1 1 4 5 1 2 4 3 5 5 4 5
## [47881] 3 2 2 3 2 4 5 1 5 1 5 2 1 1 4 1 4 5 5 5 1 2 5 1 5 3 5 1 2 5 1 2 1 5 4 2
## [47917] 4 3 3 3 2 4 1 5 4 1 5 2 2 5 1 2 5 5 4 2 5 2 1 3 1 1 3 3 2 4 3 2 1 4 5 1
## [47953] 2 3 5 4 5 5 2 3 4 4 5 1 3 3 1 3 5 2 1 3 2 3 4 3 2 2 3 2 1 3 2 5 3 1 4 2
## [47989] 4 1 4 1 1 3 1 1 3 3 2 5 5 1 4 3 3 5 5 1 2 5 5 1 5 3 2 5 4 4 2 4 3 4 2 5
## [48025] 5 2 5 2 3 2 5 4 4 5 5 5 4 4 2 1 3 1 3 5 5 5 2 5 2 4 1 1 4 2 4 3 4 5 4 3
## [48061] 4 2 2 5 3 3 3 4 4 2 2 1 3 2 5 4 3 5 3 5 5 1 2 5 2 3 5 5 3 1 2 4 3 3 4 5
## [48097] 5 1 4 4 4 4 3 5 1 5 3 5 3 3 4 2 2 5 4 5 3 3 3 1 3 5 2 1 1 5 1 1 1 5 5 3
## [48133] 1 4 4 4 5 3 3 2 2 2 5 5 4 3 4 1 5 3 1 5 1 2 4 1 5 4 1 4 3 2 1 5 3 1 2 5
## [48169] 4 1 5 3 5 2 4 1 2 4 4 1 5 3 3 2 4 4 4 3 3 5 3 1 5 5 4 4 2 3 5 1 4 1 4 1
## [48205] 3 4 5 2 3 5 4 2 5 2 4 2 3 2 5 3 4 4 1 3 1 4 1 2 1 4 3 5 4 2 2 5 1 5 5 2
## [48241] 4 2 2 4 5 5 3 4 3 5 2 3 4 1 4 2 2 4 3 5 1 3 1 2 1 4 5 4 5 2 5 2 5 5 4 4
## [48277] 5 3 2 1 5 2 2 5 5 5 3 4 2 3 5 5 1 5 4 1 3 2 4 5 5 3 2 5 5 2 4 2 4 4 1 1
## [48313] 2 3 5 3 5 4 1 3 2 1 5 4 1 3 3 3 1 5 2 4 3 2 1 3 2 2 5 2 1 1 3 2 1 1 1 4
## [48349] 4 3 1 2 5 2 5 3 4 1 3 4 2 1 2 5 3 4 4 4 4 5 1 3 5 1 1 5 2 3 1 5 5 1 2 3
## [48385] 2 5 2 2 5 2 2 5 2 4 3 1 4 3 5 1 2 3 2 5 5 1 1 2 3 5 4 1 1 4 2 5 2 1 1 2
## [48421] 2 3 5 2 1 3 5 5 2 3 3 1 2 4 2 4 3 1 5 1 3 1 3 3 1 3 1 1 3 1 5 3 1 1 3 5
## [48457] 3 5 5 4 3 1 5 2 5 5 2 5 2 3 1 2 3 2 4 5 4 2 1 2 5 3 4 2 4 2 3 4 1 4 2 5
## [48493] 5 4 1 3 3 2 2 2 3 2 3 1 3 5 2 4 1 2 1 1 4 4 1 1 2 4 5 3 5 5 4 4 1 1 2 2
## [48529] 1 3 2 2 2 1 3 3 3 4 4 2 3 1 5 2 1 3 3 4 5 2 3 4 1 2 5 3 2 2 5 4 3 4 3 4
## [48565] 1 5 2 5 5 2 1 4 1 4 3 5 4 1 5 5 2 1 4 1 1 3 2 5 2 3 3 5 3 1 3 1 2 4 2 2
## [48601] 4 5 2 4 5 3 4 1 3 2 3 3 2 2 3 2 4 4 2 1 4 5 5 3 1 5 3 1 2 1 4 1 2 4 3 4
## [48637] 5 2 2 5 2 3 5 2 3 2 5 3 5 3 2 4 5 5 4 2 4 1 1 3 1 1 4 4 5 4 5 4 3 1 1 3
## [48673] 2 1 1 3 3 2 4 1 2 4 4 2 4 2 3 2 4 3 1 4 1 5 3 3 3 4 2 1 4 2 1 3 3 1 3 1
## [48709] 3 4 4 2 1 1 3 1 3 4 4 4 4 4 5 5 1 3 4 4 2 3 2 2 5 3 2 1 3 3 5 4 1 4 4 3
## [48745] 5 2 2 4 4 5 2 4 4 3 1 2 2 4 5 4 1 4 2 5 2 4 3 3 4 4 2 3 5 4 5 5 5 1 2 4
## [48781] 5 1 3 1 4 1 4 3 5 3 2 1 5 5 1 2 4 1 3 3 2 3 1 4 2 5 5 5 1 2 5 5 2 2 2 4
## [48817] 1 3 4 5 1 2 3 5 4 1 1 5 3 3 4 4 1 5 1 5 2 4 4 4 4 5 3 4 3 4 1 1 2 4 5 3
## [48853] 5 3 5 1 1 4 1 5 5 5 2 1 1 2 4 4 5 1 3 1 2 3 3 3 5 1 4 5 5 5 3 2 5 4 4 2
## [48889] 2 2 1 1 4 4 2 4 5 2 4 4 5 3 2 2 2 3 4 3 1 1 4 4 5 3 1 3 3 5 1 3 2 4 1 4
## [48925] 2 3 4 4 2 3 1 3 1 3 3 3 2 3 4 2 4 5 1 5 1 3 2 3 4 2 1 4 1 1 4 4 4 4 1 2
## [48961] 3 2 5 3 1 1 5 4 2 1 4 4 4 2 4 4 1 2 4 1 3 2 4 4 1 5 3 1 1 2 3 1 3 5 5 1
## [48997] 5 3 1 5 2 1 4 1 1 4 2 4 3 4 1 1 1 5 4 2 1 5 4 2 5 3 2 2 5 1 1 4 5 5 5 2
## [49033] 5 3 4 2 4 2 1 1 1 1 5 1 4 1 2 5 2 3 1 4 2 3 4 3 5 1 5 3 5 3 4 2 2 2 3 2
## [49069] 3 2 5 1 5 5 2 1 1 1 3 4 1 1 3 1 3 3 1 4 5 1 2 2 4 4 1 1 1 3 2 5 5 4 4 2
## [49105] 1 1 1 1 1 3 1 5 5 2 1 1 3 4 2 2 3 1 4 4 3 1 1 3 1 5 1 4 3 3 4 5 3 1 3 4
## [49141] 1 1 5 3 2 4 2 4 1 5 2 2 4 2 2 4 1 3 4 5 1 1 4 4 4 3 3 1 3 1 3 3 4 3 3 1
## [49177] 2 3 4 2 1 5 1 4 3 5 5 4 3 5 4 1 1 2 4 1 3 2 5 1 3 3 3 4 4 5 1 1 5 3 5 4
## [49213] 1 1 4 4 5 4 2 2 4 5 2 3 4 3 2 5 5 4 1 3 2 1 4 2 3 2 4 2 1 5 5 1 3 2 3 1
## [49249] 3 3 2 4 2 2 2 4 5 3 2 4 4 2 2 2 4 5 1 3 5 4 3 4 3 5 3 4 2 1 3 4 4 4 4 5
## [49285] 4 3 2 5 3 5 4 5 2 4 2 5 1 4 2 5 4 1 4 4 1 3 5 3 4 1 1 4 4 4 3 2 1 3 1 4
## [49321] 5 1 3 2 4 3 1 4 3 1 4 1 2 1 3 3 1 5 2 1 2 1 5 5 3 1 1 5 3 1 1 4 5 3 3 4
## [49357] 4 3 3 1 2 4 5 5 3 5 1 3 1 4 5 2 3 4 5 4 5 2 3 2 1 5 1 5 2 4 3 1 1 2 4 3
## [49393] 1 4 5 5 5 5 1 3 3 5 2 2 1 4 5 3 1 3 5 4 5 5 2 5 3 5 3 2 2 3 4 5 2 2 4 3
## [49429] 5 1 5 5 3 1 2 1 1 4 5 5 2 2 3 3 1 3 1 1 3 1 5 5 2 4 1 4 4 5 2 1 3 4 1 3
## [49465] 4 3 3 4 1 3 2 5 2 3 3 4 5 1 3 3 5 2 5 5 3 3 5 1 1 2 1 4 3 2 1 5 1 4 2 2
## [49501] 3 3 3 4 2 3 3 4 5 5 5 2 4 3 1 4 2 2 2 5 1 3 2 2 4 2 1 1 3 2 2 3 2 4 4 3
## [49537] 5 3 2 4 3 2 3 4 3 5 1 1 2 3 4 1 4 1 1 3 1 3 2 2 2 2 4 3 4 3 5 4 2 3 3 4
## [49573] 1 1 3 1 1 4 2 4 5 1 5 1 3 5 4 1 4 1 5 5 5 1 4 4 2 4 2 4 2 5 5 5 2 5 4 3
## [49609] 1 3 2 5 5 1 2 5 3 4 3 2 4 4 3 1 1 1 1 1 5 2 3 5 1 1 3 5 5 4 3 1 5 2 1 3
## [49645] 4 2 2 1 4 4 1 4 2 1 4 3 2 2 1 4 2 2 5 1 3 1 3 5 2 2 2 5 3 4 5 5 2 4 2 2
## [49681] 4 5 4 5 2 1 2 5 2 2 2 4 1 2 3 2 2 5 4 5 4 5 1 3 5 1 2 5 4 3 3 3 5 1 1 2
## [49717] 5 3 1 5 2 4 5 4 4 1 2 2 5 4 2 5 2 2 3 5 2 4 5 5 4 2 4 3 5 5 4 3 5 3 5 4
## [49753] 2 5 1 1 2 4 2 2 1 5 2 2 2 2 4 4 4 4 4 1 5 3 5 4 5 2 3 1 3 4 5 4 4 2 2 1
## [49789] 1 5 1 5 3 4 1 4 1 1 2 3 4 4 2 1 5 1 3 3 2 4 3 2 2 1 5 2 2 4 2 5 1 5 4 3
## [49825] 5 4 5 3 5 3 3 1 1 4 4 1 4 2 2 4 5 2 1 4 3 2 4 1 1 2 3 2 3 3 3 3 1 1 3 3
## [49861] 3 2 3 5 3 5 2 1 5 3 1 4 3 3 4 3 3 1 4 2 4 4 2 5 3 1 2 4 5 1 5 5 3 2 2 3
## [49897] 4 1 4 4 1 2 2 1 1 3 2 5 5 4 3 2 4 2 1 2 4 2 3 2 1 2 3 3 2 5 5 2 3 1 3 3
## [49933] 2 3 3 5 2 2 3 2 4 2 3 4 5 1 5 1 1 5 3 5 5 3 3 1 2 5 5 4 1 5 4 1 4 2 1 1
## [49969] 3 1 5 3 4 2 4 2 1 3 3 2 4 3 4 5 2 5 5 4 3 5 2 3 5 2 1 5 5 3 1 2 5 2 5 4
## [50005] 4 3 3 1 2 4 2 1 1 4 1 3 2 3 2 1 4 4 3 2 1 2 5 2 5 4 1 5 1 1 1 4 3 4 2 3
## [50041] 1 2 4 1 1 2 4 2 1 4 1 4 3 3 4 4 4 4 4 4 4 3 2 2 3 4 3 2 3 4 2 2 4 4 2 2
## [50077] 5 3 4 1 1 4 1 3 5 5 2 2 2 4 3 1 1 5 4 3 5 3 3 3 3 2 1 3 2 3 5 1 5 1 5 2
## [50113] 4 5 2 4 1 4 4 2 4 2 3 4 3 2 2 2 4 3 1 2 1 1 1 1 4 2 1 3 1 2 4 4 1 3 2 4
## [50149] 5 4 3 3 1 5 3 2 1 1 3 4 4 4 1 4 1 1 1 3 1 4 5 2 3 5 1 2 3 3 5 1 2 4 5 1
## [50185] 1 2 1 4 4 1 4 2 3 3 4 5 4 3 3 3 2 2 1 5 2 3 1 3 4 5 1 3 4 2 4 3 1 5 4 5
## [50221] 3 4 4 5 1 3 3 1 4 4 4 3 3 1 5 4 2 1 5 2 2 4 1 4 4 5 1 2 2 4 1 2 3 2 2 4
## [50257] 4 3 2 5 1 4 2 3 4 5 2 2 4 5 3 3 4 1 2 1 2 1 1 5 2 3 1 5 3 5 2 3 1 2 1 3
## [50293] 1 1 4 3 1 4 3 4 5 5 2 2 5 2 1 5 1 2 3 4 3 1 2 2 1 3 3 5 2 5 1 5 5 2 4 2
## [50329] 5 2 1 1 4 5 2 1 1 5 1 5 4 3 2 3 3 2 5 4 1 5 4 2 5 2 4 2 5 3 4 4 2 3 4 5
## [50365] 1 3 5 5 3 2 3 2 2 2 5 3 2 3 2 1 5 1 1 3 1 5 2 4 3 2 4 1 5 2 2 1 3 1 1 1
## [50401] 2 1 2 1 5 2 5 3 3 4 4 1 1 3 3 1 4 3 4 3 3 5 3 5 4 1 5 1 1 2 2 5 5 1 5 4
## [50437] 5 5 4 5 1 2 2 2 5 5 3 3 1 5 2 4 4 2 5 1 5 3 5 1 5 4 3 5 2 4 4 5 4 2 2 2
## [50473] 2 3 2 5 4 3 1 3 1 1 5 5 2 5 2 5 3 2 5 4 3 4 3 5 5 3 1 4 4 3 2 3 5 2 1 1
## [50509] 5 2 1 1 3 1 2 5 3 2 1 2 5 4 4 4 3 5 4 2 3 1 2 2 2 5 2 4 4 4 4 2 2 3 5 5
## [50545] 4 3 5 2 1 1 3 4 1 4 4 4 4 5 4 3 4 1 3 3 1 2 2 2 3 2 4 5 5 3 2 5 1 3 5 1
## [50581] 2 5 2 2 4 3 2 2 1 2 3 1 3 5 1 3 5 2 5 3 3 5 5 4 5 5 4 5 2 4 4 2 2 3 3 1
## [50617] 5 4 5 3 4 5 3 1 4 3 1 2 1 1 5 2 2 3 5 4 2 4 2 3 5 1 5 2 5 3 5 5 5 3 1 4
## [50653] 4 1 4 5 2 3 1 4 2 3 2 5 4 1 4 3 5 5 2 5 3 5 4 2 1 3 4 3 5 5 2 5 4 4 3 1
## [50689] 2 3 2 2 1 5 4 1 2 2 1 5 1 3 4 1 3 3 3 5 1 4 2 1 3 5 4 1 2 1 3 2 4 1 5 2
## [50725] 1 5 4 4 5 3 3 5 2 2 4 3 3 3 5 5 3 1 3 5 3 5 4 4 1 2 2 1 2 4 5 3 3 3 3 4
## [50761] 5 3 1 3 5 5 4 4 4 5 4 5 5 2 1 2 1 4 5 4 4 5 4 4 5 5 1 2 1 5 2 2 1 2 4 5
## [50797] 3 3 4 1 3 5 4 3 3 3 1 4 1 5 5 2 5 3 1 5 3 4 1 5 1 3 3 4 2 3 2 1 1 4 1 1
## [50833] 5 1 4 2 1 4 1 5 2 5 1 3 5 1 5 4 1 1 4 4 1 2 2 4 1 2 5 4 2 1 2 4 1 2 1 1
## [50869] 5 3 1 5 2 3 4 5 3 5 2 1 1 4 5 2 4 3 4 3 3 2 5 3 4 4 2 1 2 3 5 1 1 5 2 1
## [50905] 3 4 3 5 2 1 2 5 4 5 5 3 5 4 4 3 4 5 2 3 5 1 4 3 4 3 5 2 2 3 1 1 1 4 4 4
## [50941] 4 4 1 5 1 1 3 5 1 4 5 2 1 1 4 3 1 3 1 2 5 1 3 1 5 4 5 3 3 3 3 4 2 2 4 2
## [50977] 5 5 2 5 5 3 2 1 5 3 2 4 4 3 2 5 2 3 2 1 2 2 3 5 2 1 4 5 1 5 5 2 4 3 2 1
## [51013] 1 3 5 2 2 5 3 1 5 4 3 1 5 5 3 2 4 2 4 5 4 2 5 5 4 5 3 5 3 3 5 2 2 1 3 4
## [51049] 4 3 1 2 1 3 4 2 2 4 3 1 4 5 3 5 3 1 2 3 3 5 3 3 2 1 1 1 4 1 1 2 1 3 3 2
## [51085] 3 2 3 5 1 2 5 5 3 4 3 2 1 5 3 3 2 1 3 2 2 4 2 5 5 5 1 4 5 1 2 4 3 3 5 1
## [51121] 2 5 4 1 5 2 4 5 5 3 3 2 3 2 2 2 1 5 5 5 2 2 1 5 4 2 3 5 1 3 1 1 4 3 1 3
## [51157] 2 3 1 2 5 3 1 1 4 1 1 3 1 5 1 2 5 3 4 2 1 1 2 3 4 5 1 2 4 2 1 4 2 3 3 5
## [51193] 3 4 2 1 5 1 3 3 5 5 2 3 1 2 4 3 4 4 4 1 3 1 5 3 4 3 4 1 3 5 4 3 5 4 4 5
## [51229] 3 1 2 3 5 2 2 4 1 2 2 4 3 3 2 5 4 2 5 1 4 3 4 1 1 2 5 5 5 4 1 1 3 4 1 1
## [51265] 2 2 1 2 3 3 4 5 5 5 3 3 3 5 1 4 5 3 2 2 5 4 4 1 1 3 2 3 4 1 4 2 3 3 2 3
## [51301] 1 1 5 5 5 4 3 2 5 5 2 3 1 5 1 1 2 4 1 3 1 1 5 2 4 2 4 1 1 2 1 3 2 2 2 5
## [51337] 2 1 3 2 5 4 4 2 1 3 2 5 5 3 3 2 3 1 1 3 3 5 3 3 1 1 4 2 3 5 3 5 2 4 2 4
## [51373] 4 5 1 4 2 3 4 4 4 2 5 3 2 3 1 2 3 3 1 5 4 5 2 2 1 5 3 5 4 4 5 5 3 2 2 4
## [51409] 2 5 4 5 1 5 4 2 4 3 5 4 5 3 1 1 3 5 1 4 1 1 3 4 2 1 2 4 4 4 5 4 1 4 4 5
## [51445] 4 4 1 3 1 1 4 2 1 2 4 1 1 1 5 3 2 4 3 4 2 2 4 5 3 5 1 5 5 4 1 3 4 4 4 5
## [51481] 4 2 5 1 3 4 1 3 3 5 3 2 2 4 2 2 5 2 2 2 4 3 5 3 5 2 4 1 3 5 5 5 2 5 5 3
## [51517] 4 1 1 2 4 4 3 4 4 5 2 2 1 1 3 3 1 4 3 5 3 5 2 3 5 2 4 5 3 2 3 5 5 1 4 1
## [51553] 1 5 4 1 5 4 1 1 1 4 5 3 5 1 1 1 3 5 1 5 4 5 3 2 3 3 5 4 3 4 5 4 4 1 1 1
## [51589] 4 2 4 1 3 2 5 5 1 5 2 1 5 4 5 4 1 5 2 4 1 4 1 4 4 3 5 5 1 3 5 3 4 3 3 1
## [51625] 5 1 5 1 2 2 5 1 5 5 4 3 3 5 4 1 1 2 3 3 3 4 4 3 5 3 1 2 2 4 5 1 3 1 4 3
## [51661] 5 5 2 5 2 3 1 5 5 1 5 5 1 5 4 4 3 3 3 2 3 3 4 1 2 4 3 2 5 3 4 2 5 3 4 1
## [51697] 4 1 4 4 5 4 4 4 2 1 2 5 3 3 3 1 4 3 3 3 5 3 2 2 2 1 5 5 2 1 2 2 4 2 1 3
## [51733] 5 3 2 1 3 4 4 5 3 5 2 1 5 2 4 2 4 2 3 5 4 3 1 2 2 4 1 4 3 2 3 1 2 4 4 4
## [51769] 5 4 3 3 4 5 4 2 4 3 2 1 2 5 3 1 1 1 2 5 2 3 5 4 2 4 1 2 3 2 2 4 3 1 5 2
## [51805] 2 1 4 1 1 1 1 4 2 4 3 4 4 2 1 3 4 5 5 4 4 4 5 4 2 1 5 3 2 4 2 4 5 5 5 4
## [51841] 2 1 1 1 1 2 2 2 1 5 2 4 4 4 3 2 5 5 1 1 3 4 3 2 3 5 5 2 5 4 5 4 4 1 1 1
## [51877] 3 5 1 5 4 1 4 1 1 4 5 2 5 4 4 1 2 4 3 2 4 1 2 1 5 1 4 3 1 2 4 4 2 4 2 5
## [51913] 4 1 3 1 3 2 1 3 4 3 3 4 2 4 1 3 4 2 4 2 2 1 5 4 3 5 1 2 3 5 1 1 4 2 3 5
## [51949] 4 3 4 1 3 1 3 4 2 5 4 4 3 3 3 3 5 2 5 1 4 4 3 4 1 5 2 1 5 1 4 4 2 4 1 5
## [51985] 5 1 2 5 2 3 2 3 3 1 5 2 5 4 2 1 3 5 4 4 3 5 1 5 5 5 3 1 3 5 5 5 4 3 1 5
## [52021] 3 2 1 1 1 3 2 2 3 5 5 1 2 5 5 1 1 4 1 2 5 3 4 1 4 3 4 3 3 2 1 2 3 3 4 1
## [52057] 3 1 5 5 4 1 3 3 2 5 1 4 2 3 2 4 4 1 5 5 4 2 4 1 1 1 3 1 1 1 2 5 5 2 1 2
## [52093] 1 3 4 1 5 3 2 2 3 1 4 5 3 3 4 1 4 4 1 3 2 5 5 4 1 3 5 5 5 4 2 1 5 1 2 4
## [52129] 2 3 2 3 5 2 2 1 4 2 2 5 5 1 5 2 4 3 1 4 2 3 3 3 1 5 5 3 4 5 4 2 2 2 5 3
## [52165] 5 4 4 4 1 5 5 2 1 5 1 5 4 2 3 1 5 2 5 2 3 3 2 1 2 1 1 5 1 2 5 4 1 5 1 1
## [52201] 5 2 3 1 1 2 3 1 1 2 5 4 4 3 2 4 3 4 4 4 2 4 1 1 1 4 5 5 3 4 1 1 5 3 4 2
## [52237] 4 2 3 2 4 2 2 1 4 1 4 1 5 3 3 4 5 2 4 1 5 2 2 5 3 3 5 3 1 5 3 1 3 4 4 3
## [52273] 4 4 2 1 5 2 1 4 1 1 2 5 2 4 3 2 3 1 2 2 3 2 2 5 3 4 2 2 5 3 4 5 1 3 1 2
## [52309] 2 5 3 2 5 4 4 3 2 3 3 3 5 3 2 2 2 5 3 3 2 5 2 5 2 1 1 4 2 3 3 5 5 1 1 4
## [52345] 3 1 3 2 2 5 5 3 1 3 3 2 3 5 4 2 2 4 1 5 3 4 4 5 2 4 1 2 2 3 3 2 2 3 1 1
## [52381] 5 3 2 1 5 2 4 5 3 2 3 3 5 2 2 2 3 2 1 2 4 1 4 1 3 4 2 1 1 4 4 5 4 4 4 4
## [52417] 4 3 2 1 3 4 5 1 2 5 2 2 2 4 5 1 3 4 5 4 1 2 5 3 4 2 5 1 3 2 4 3 4 2 4 3
## [52453] 4 3 5 4 4 5 4 2 4 4 3 1 2 1 1 1 1 3 3 1 4 5 3 1 1 4 2 5 2 5 3 5 4 3 4 4
## [52489] 5 2 2 2 2 5 2 5 2 5 2 2 4 1 5 3 4 2 1 1 2 4 2 2 4 5 5 4 2 4 3 1 3 1 4 2
## [52525] 4 1 3 2 1 1 4 1 3 3 3 1 1 1 3 3 4 3 5 2 5 3 1 4 5 5 2 2 4 1 1 1 4 4 3 4
## [52561] 2 5 5 3 4 3 5 4 2 2 4 2 5 4 2 4 2 5 2 5 2 5 1 4 4 2 1 4 3 4 4 4 1 5 1 2
## [52597] 5 1 5 4 5 1 2 1 2 4 4 4 1 2 1 2 5 3 1 5 4 4 3 2 1 4 2 5 1 1 4 2 3 2 2 4
## [52633] 2 2 4 4 3 2 5 5 3 3 1 5 3 1 4 2 1 5 1 5 1 4 3 1 1 1 4 5 4 2 1 4 1 3 1 5
## [52669] 3 4 5 2 4 5 4 4 4 1 1 3 4 1 4 3 1 1 3 2 1 3 3 2 1 1 2 2 5 1 1 1 1 2 4 4
## [52705] 2 2 5 1 4 4 3 5 1 3 4 2 4 3 5 2 5 3 4 5 1 5 3 5 1 4 2 3 3 1 2 2 2 5 1 5
## [52741] 3 3 2 1 5 3 1 3 5 1 4 3 2 5 4 1 1 2 1 5 5 3 1 3 2 1 3 5 2 4 4 5 5 2 3 5
## [52777] 3 1 5 3 4 2 4 1 3 2 4 4 5 1 3 3 4 3 3 3 2 2 4 1 5 2 3 3 3 3 1 1 3 1 4 3
## [52813] 1 3 4 5 3 3 1 1 5 4 3 3 1 1 1 1 3 1 5 5 5 2 5 1 4 5 2 2 1 2 2 3 2 1 1 2
## [52849] 3 1 4 5 1 1 2 4 3 1 1 2 2 4 1 3 2 5 3 4 5 1 2 2 3 4 2 1 4 4 3 5 1 2 3 5
## [52885] 4 1 3 3 3 3 2 1 5 1 1 4 4 4 3 1 4 5 1 5 2 4 4 4 4 5 5 5 3 2 1 5 5 1 5 1
## [52921] 4 3 3 4 4 3 4 1 3 1 1 1 2 2 1 5 2 1 2 3 5 1 5 3 5 5 2 4 5 4 1 4 5 3 3 1
## [52957] 4 1 1 3 5 5 4 1 2 2 2 3 3 5 2 5 1 1 5 5 1 5 3 3 4 1 2 2 4 2 1 5 2 5 3 2
## [52993] 4 2 5 2 2 3 3 5 1 3 2 4 2 1 4 1 5 5 2 2 4 5 2 2 3 2 1 4 1 2 3 3 3 4 4 4
## [53029] 5 2 2 2 2 2 2 1 3 1 5 3 5 2 1 1 2 2 1 4 1 5 5 2 2 5 1 1 5 2 4 1 3 1 1 1
## [53065] 3 4 5 1 1 3 3 1 4 2 3 1 3 2 5 4 2 3 1 2 3 2 1 1 4 5 1 4 5 5 2 3 3 4 3 1
## [53101] 5 1 5 2 5 2 4 2 5 4 4 4 3 3 1 3 3 5 5 2 2 4 5 3 5 4 5 2 5 3 2 3 3 5 5 3
## [53137] 5 3 1 5 1 3 5 4 5 1 2 3 1 2 2 4 2 2 3 2 2 4 4 3 5 5 1 2 4 3 4 4 2 1 3 4
## [53173] 5 1 4 3 1 4 1 2 5 5 5 5 1 5 4 1 5 4 2 2 3 4 2 5 2 2 2 4 3 5 4 4 5 3 3 4
## [53209] 3 2 2 4 2 3 2 1 2 5 5 3 1 1 5 1 1 4 1 4 2 4 2 5 2 3 2 1 3 4 4 5 5 5 2 4
## [53245] 1 2 3 1 3 2 1 2 5 4 5 2 3 3 5 1 1 1 5 5 2 3 4 5 3 1 5 4 2 2 2 2 3 1 5 1
## [53281] 4 1 2 1 4 4 4 2 3 1 3 1 2 3 3 5 4 5 1 3 2 4 4 3 1 2 4 5 2 2 5 5 4 4 1 1
## [53317] 1 1 2 1 1 5 1 1 5 2 3 5 5 5 5 3 4 5 3 5 3 4 2 3 3 1 5 4 1 1 4 4 1 5 5 5
## [53353] 2 3 4 1 5 4 3 1 4 4 5 5 2 4 4 1 2 5 3 2 1 1 2 5 2 5 4 5 3 2 3 2 2 3 1 4
## [53389] 3 5 1 5 4 5 1 1 4 2 2 1 3 4 2 2 3 2 1 3 5 2 5 4 3 5 2 2 4 4 5 4 3 2 5 4
## [53425] 2 5 4 5 1 2 1 5 1 3 2 3 5 4 1 2 2 2 5 4 4 1 1 4 4 4 1 3 5 2 3 5 1 1 2 2
## [53461] 1 4 2 1 3 1 1 2 2 4 4 2 1 4 1 4 3 5 4 2 5 4 3 1 4 5 3 4 5 4 4 2 4 1 5 5
## [53497] 1 5 1 3 3 2 1 1 2 2 1 3 2 3 3 3 2 1 2 1 1 1 2 3 5 3 2 3 4 3 5 4 5 1 5 1
## [53533] 4 3 4 5 2 2 3 2 3 1 3 3 1 5 3 3 1 3 2 2 1 4 4 3 5 5 3 3 5 3 1 2 5 3 4 4
## [53569] 4 1 3 5 4 3 5 2 4 4 2 4 2 5 3 2 2 4 4 4 3 4 4 4 2 4 3 4 3 5 4 4 2 4 1 4
## [53605] 4 1 2 1 4 3 5 4 5 4 4 4 2 2 5 1 1 5 2 2 5 1 2 1 3 2 1 4 3 3 2 5 1 4 5 1
## [53641] 4 2 3 5 4 4 5 2 2 5 4 2 2 1 2 3 3 5 4 5 2 1 1 5 1 3 4 3 2 3 1 3 4 4 3 1
## [53677] 2 3 1 5 2 4 1 3 4 1 3 5 1 2 4 5 1 3 1 2 1 1 3 1 4 2 3 4 1 3 1 1 3 3 1 4
## [53713] 4 1 2 5 5 3 4 3 2 2 2 2 3 5 3 1 4 2 3 1 1 2 1 4 1 4 5 5 3 3 1 4 4 2 1 2
## [53749] 2 2 5 3 2 2 4 2 3 1 2 5 4 1 5 2 1 3 1 5 4 3 3 5 1 2 3 5 5 1 2 2 5 3 1 2
## [53785] 5 1 5 4 4 4 1 2 5 5 1 4 1 5 4 1 4 5 5 5 3 4 5 3 3 4 1 5 3 1 5 4 3 3 3 4
## [53821] 5 1 4 5 4 5 1 4 3 2 4 4 1 2 5 5 5 2 2 4 1 2 5 1 1 5 2 5 2 2 4 4 1 1 3 2
## [53857] 1 1 2 4 2 3 5 2 5 1 4 2 4 2 5 2 2 3 4 5 1 1 3 5 3 1 5 1 4 1 1 5 1 4 5 2
## [53893] 5 3 3 3 5 3 3 5 4 3 2 1 3 4 3 3 5 3 4 3 2 4 2 4 3 3 4 5 4 3 5 3 5 4 5 1
## [53929] 3 1 1 1 3 4 1 2 1 4 3 2 2 3 3 4 1 2 5 4 4 5 4 4 3 5 1 2 4 5 2 5 5 5 4 2
## [53965] 3 5 2 5 3 1 4 3 3 4 2 4 5 1 2 3 4 1 2 5 2 5 2 2 1 1 2 5 2 3 5 4 2 3 2 4
## [54001] 2 4 1 1 4 1 2 1 3 1 1 5 2 4 1 5 5 1 1 4 3 4 1 3 4 2 4 1 3 2 5 3 3 2 3 4
## [54037] 3 1 1 4 3 4 5 2 4 4 4 3 5 1 1 1 4 3 5 5 2 2 4 1 1 4 3 5 5 3 2 1 3 2 4 3
## [54073] 1 4 2 4 4 1 3 3 2 4 3 3 4 3 5 2 5 1 5 2 1 4 5 3 5 3 4 5 1 4 3 1 2 2 4 3
## [54109] 2 4 3 3 5 1 3 4 1 4 3 3 1 1 1 5 3 4 1 5 2 5 4 2 4 5 5 3 2 5 5 3 1 5 3 2
## [54145] 5 3 4 4 4 4 5 2 5 2 1 1 1 3 2 5 5 4 4 1 2 1 4 5 4 4 3 4 4 4 4 4 4 4 5 4
## [54181] 3 3 5 2 5 5 2 4 4 4 3 4 2 3 5 3 2 2 4 4 1 3 3 1 3 3 2 3 5 5 4 3 4 4 5 1
## [54217] 5 5 1 3 4 2 3 3 5 5 3 2 1 4 4 2 2 3 1 3 4 2 5 1 2 2 1 3 1 4 5 4 1 1 2 1
## [54253] 5 2 5 1 5 1 5 4 4 3 4 5 2 3 3 3 1 4 2 2 2 4 3 3 2 4 2 2 3 1 3 2 4 1 5 4
## [54289] 3 4 3 3 2 3 4 3 5 1 5 2 3 5 2 3 3 3 1 3 5 5 3 5 2 4 1 1 5 4 5 1 5 2 3 2
## [54325] 5 4 4 2 5 5 3 1 5 2 3 4 1 1 3 3 1 2 2 5 1 1 2 1 5 1 5 5 1 2 2 1 4 1 4 3
## [54361] 3 4 5 2 2 4 5 2 1 3 5 2 4 5 5 2 5 3 4 1 5 4 1 2 4 1 3 2 4 4 1 5 1 3 2 5
## [54397] 5 3 2 2 3 3 2 1 5 3 3 3 1 2 5 3 4 1 2 1 2 4 4 2 2 3 4 3 2 3 3 5 3 1 3 4
## [54433] 4 2 4 3 5 4 2 2 1 2 1 3 4 4 2 2 3 2 3 1 5 3 3 1 5 1 4 1 5 3 4 2 2 1 2 5
## [54469] 5 5 4 1 5 4 4 5 5 1 4 4 1 1 4 3 3 2 5 5 4 4 1 1 3 2 5 3 2 3 3 3 3 2 2 2
## [54505] 3 1 1 1 4 1 4 5 4 4 2 5 5 5 5 1 5 4 5 1 1 4 4 2 2 2 5 1 5 4 3 4 1 2 2 4
## [54541] 4 3 3 4 1 4 4 1 4 4 2 4 2 2 1 2 5 3 4 2 1 3 5 4 4 2 1 5 4 1 2 1 2 1 3 1
## [54577] 3 3 3 5 5 4 4 4 1 5 5 2 2 1 5 3 5 3 2 2 1 1 4 4 2 3 5 5 2 5 1 4 2 2 4 5
## [54613] 5 4 4 5 3 5 4 5 5 5 1 2 1 4 4 3 5 4 4 5 1 3 4 1 4 1 5 3 2 3 2 4 4 1 5 5
## [54649] 1 1 3 4 4 3 3 5 3 4 5 2 1 5 3 5 2 2 4 2 3 4 5 3 2 4 1 2 3 5 5 3 3 3 2 3
## [54685] 1 5 1 5 3 2 2 4 3 4 2 4 2 4 2 3 4 4 3 1 4 4 1 3 2 3 2 2 2 2 5 2 3 4 3 2
## [54721] 1 5 4 5 3 2 2 5 2 1 1 3 2 3 5 2 1 5 1 2 2 1 5 3 5 4 1 3 4 4 4 3 4 4 1 4
## [54757] 4 2 1 2 1 2 1 5 3 3 5 1 4 1 2 2 3 5 3 4 1 2 1 2 5 2 3 5 3 4 2 1 5 5 3 4
## [54793] 4 2 3 4 4 5 2 5 1 2 5 5 4 2 3 5 5 4 2 4 3 5 3 5 2 3 2 3 4 3 4 3 1 3 4 5
## [54829] 4 2 4 4 2 2 5 2 1 2 2 3 4 2 5 1 2 3 3 3 3 4 3 4 1 5 5 1 5 3 2 2 2 4 1 1
## [54865] 4 1 2 3 5 2 5 4 3 1 5 1 4 1 4 2 1 1 3 5 2 5 5 1 4 5 2 3 3 1 4 1 5 3 3 5
## [54901] 1 2 2 3 2 4 4 5 5 4 4 4 1 1 1 3 3 3 5 1 5 2 4 3 4 1 1 3 1 3 3 1 5 1 4 4
## [54937] 3 1 3 2 4 4 4 5 3 1 1 1 5 5 4 3 3 2 3 1 2 4 3 3 2 2 4 4 4 5 3 5 1 3 3 1
## [54973] 4 5 5 5 3 5 5 4 5 5 5 2 5 4 4 4 5 5 2 5 3 4 4 3 1 2 2 5 2 4 5 4 2 5 3 5
## [55009] 4 3 2 1 4 5 1 3 1 5 5 1 4 1 1 4 4 5 1 3 5 1 1 4 4 1 3 1 3 3 3 4 1 1 1 4
## [55045] 5 4 2 4 2 5 3 1 5 1 4 3 5 1 1 1 1 5 3 3 4 1 5 2 4 4 3 1 3 5 3 2 4 3 3 4
## [55081] 2 4 2 2 5 4 3 2 5 5 5 3 1 3 5 4 3 4 3 3 1 2 2 1 5 4 5 5 1 2 4 4 2 5 4 2
## [55117] 5 3 1 4 1 3 2 1 4 5 1 5 2 1 2 3 3 1 3 3 2 3 3 4 5 4 4 5 1 1 3 2 3 5 5 3
## [55153] 2 2 4 3 1 2 4 4 4 2 5 3 4 2 5 5 4 5 4 3 4 1 2 4 5 5 5 1 3 1 5 3 1 5 5 1
## [55189] 1 4 4 4 1 4 4 2 4 1 5 5 2 3 4 2 3 3 3 2 4 2 1 1 4 5 2 5 2 2 5 5 3 1 2 5
## [55225] 4 3 5 5 4 3 1 4 2 2 3 3 1 5 3 4 1 4 3 1 2 4 3 3 2 4 1 4 4 4 5 5 5 3 3 3
## [55261] 2 3 4 4 4 2 4 2 2 4 3 1 2 5 3 3 3 3 1 1 1 5 2 1 2 2 5 3 1 1 5 4 3 2 1 4
## [55297] 1 1 2 3 2 2 1 3 1 3 2 3 1 2 5 2 3 1 3 2 5 2 1 3 1 4 3 2 1 5 4 1 3 1 5 2
## [55333] 2 4 5 1 3 2 3 5 3 1 5 3 1 3 3 2 5 2 2 5 2 5 1 5 4 4 5 5 4 2 4 3 2 1 1 4
## [55369] 3 1 2 2 5 1 3 4 1 3 1 4 4 4 3 5 4 2 1 3 4 4 1 3 1 2 3 4 1 1 3 5 4 5 3 4
## [55405] 5 3 4 2 1 5 3 2 4 5 5 2 2 5 2 5 2 4 3 2 5 3 5 4 4 4 5 5 4 1 5 1 4 1 1 3
## [55441] 3 5 3 3 5 3 1 5 1 3 4 3 5 2 4 3 1 2 1 3 1 2 5 1 3 5 2 4 2 3 1 5 3 3 1 4
## [55477] 4 1 2 3 3 1 5 5 4 2 2 5 3 3 4 3 2 2 5 3 4 2 3 5 5 5 1 3 3 4 3 5 1 5 4 3
## [55513] 5 4 2 2 5 4 3 1 5 5 4 2 5 5 5 5 1 4 2 4 1 4 2 4 4 1 4 5 3 4 1 5 5 1 1 5
## [55549] 2 2 1 3 3 4 3 3 1 3 3 3 1 3 4 3 4 1 1 4 4 3 4 1 1 1 3 4 1 1 4 1 5 4 2 4
## [55585] 1 1 3 1 2 2 5 1 3 4 1 1 1 4 5 5 5 1 5 4 4 3 1 3 5 2 5 4 2 4 1 3 1 4 4 1
## [55621] 4 2 2 5 3 3 2 1 3 2 3 5 1 4 2 1 5 2 1 3 5 2 2 3 1 5 5 1 4 5 5 1 4 2 1 3
## [55657] 2 4 1 1 4 3 1 2 2 4 4 1 2 4 5 4 1 4 4 1 2 3 2 5 5 5 1 2 3 1 4 3 1 5 2 2
## [55693] 4 3 4 3 5 4 4 2 4 1 3 1 1 1 2 5 3 5 3 5 4 3 3 5 4 1 4 2 2 2 4 5 3 4 4 1
## [55729] 3 1 1 5 2 1 4 4 1 1 3 4 2 4 1 3 2 2 5 1 3 2 4 3 4 5 3 4 1 4 5 4 1 3 1 5
## [55765] 4 1 2 2 5 1 4 1 4 1 5 4 1 1 2 3 5 3 2 1 4 5 1 5 3 2 3 3 2 2 4 4 3 3 1 1
## [55801] 4 4 4 1 1 3 5 5 3 4 5 2 4 1 1 3 2 2 4 2 2 4 1 4 1 1 5 1 4 4 2 2 4 2 3 3
## [55837] 4 4 3 1 2 2 5 3 5 1 4 1 2 3 5 4 3 5 5 3 5 2 2 3 2 4 2 3 4 5 1 4 5 4 5 3
## [55873] 1 2 1 2 1 2 1 5 4 1 1 2 1 3 1 5 1 5 3 5 1 5 2 2 4 1 5 3 1 3 2 4 3 4 4 1
## [55909] 1 3 3 5 2 2 4 5 4 3 5 5 5 3 5 2 5 5 2 4 1 1 1 2 4 2 3 2 1 4 3 1 1 4 2 2
## [55945] 2 2 3 3 2 1 5 5 5 5 2 1 5 2 4 2 5 2 5 2 3 3 3 5 2 3 2 4 4 2 4 4 2 3 2 4
## [55981] 2 5 5 4 3 3 1 4 3 2 3 2 3 5 3 1 3 4 2 4 4 1 5 2 2 2 1 1 2 2 5 4 4 2 2 1
## [56017] 2 4 3 1 2 4 4 1 2 2 1 2 1 2 1 5 5 4 4 5 1 3 1 3 3 5 5 3 4 2 3 4 1 4 1 4
## [56053] 3 2 2 2 1 3 3 3 4 4 5 4 5 5 5 4 4 4 1 5 2 2 2 2 1 3 3 2 4 4 4 1 5 4 3 4
## [56089] 5 3 4 5 3 1 3 5 3 5 4 5 3 3 2 4 4 4 4 5 3 2 4 1 1 2 1 2 4 3 2 2 5 1 5 5
## [56125] 2 3 2 2 4 4 1 3 4 1 1 5 1 2 3 2 3 2 2 2 4 5 1 1 2 1 3 5 3 3 3 1 4 5 5 5
## [56161] 3 4 4 5 2 4 1 5 1 4 5 2 5 2 3 4 4 1 2 3 2 2 2 5 2 4 4 4 5 3 2 2 4 5 2 1
## [56197] 4 2 5 2 4 2 5 1 3 1 5 3 5 4 3 4 4 5 3 5 4 2 4 3 3 3 3 4 3 2 1 2 2 4 4 3
## [56233] 2 1 4 4 4 2 4 2 3 4 1 5 4 5 5 2 1 2 5 3 4 2 1 4 3 3 4 2 4 3 3 4 5 3 4 5
## [56269] 2 2 4 3 4 1 2 1 1 3 4 4 4 5 2 3 3 2 1 1 3 1 2 3 2 2 3 5 5 2 3 5 2 1 2 4
## [56305] 5 3 2 3 2 3 3 1 5 2 5 5 4 3 1 4 5 1 4 1 1 4 5 5 3 2 3 2 1 5 4 5 3 4 1 3
## [56341] 4 2 2 3 5 3 4 5 3 3 2 3 2 1 4 5 2 5 4 3 5 5 2 1 3 3 2 1 2 1 1 3 2 2 3 5
## [56377] 2 2 5 2 3 4 2 4 3 4 2 4 1 4 5 5 1 1 1 1 3 1 4 1 3 5 5 5 1 2 2 5 1 1 2 2
## [56413] 5 1 3 2 5 2 4 5 2 3 4 2 5 3 3 2 3 4 3 1 1 5 5 5 1 3 3 5 3 1 1 5 5 2 4 3
## [56449] 4 3 1 2 3 5 1 5 5 3 5 3 5 2 5 2 3 3 3 4 1 5 2 3 3 4 5 5 1 4 3 5 4 2 5 4
## [56485] 5 3 1 3 5 3 4 5 4 1 4 1 4 2 5 2 3 3 5 5 2 5 5 3 2 1 3 2 4 5 4 3 1 5 1 2
## [56521] 2 2 4 4 4 5 4 4 4 5 5 2 2 2 5 5 4 2 5 5 5 1 5 1 5 4 4 1 3 1 4 4 4 1 2 5
## [56557] 4 1 1 5 5 2 4 1 3 2 4 5 1 3 2 5 1 3 2 4 2 4 1 4 2 3 3 1 3 2 4 4 3 4 3 5
## [56593] 4 5 5 5 2 1 1 3 5 1 5 5 5 5 1 5 5 4 2 2 5 2 2 5 5 2 2 3 4 3 4 1 2 2 3 2
## [56629] 2 5 2 1 4 3 4 5 4 5 2 3 1 3 5 2 4 3 2 3 5 1 1 1 1 1 1 5 2 5 1 1 1 5 1 1
## [56665] 5 4 5 1 5 2 4 1 1 1 1 5 1 5 3 4 5 3 1 1 4 2 3 5 5 4 5 2 1 4 4 1 5 3 1 2
## [56701] 5 5 3 2 5 5 1 4 3 5 1 5 3 1 4 5 2 2 1 4 4 1 3 3 5 2 1 2 2 1 3 5 5 2 1 5
## [56737] 2 4 3 4 2 4 5 4 5 1 3 1 2 1 4 1 2 3 5 4 1 1 1 4 1 1 1 2 2 5 5 5 5 3 5 5
## [56773] 4 3 5 5 2 1 3 4 1 3 4 3 4 5 2 5 1 1 5 5 2 2 3 1 3 1 4 5 4 3 4 2 1 3 3 2
## [56809] 2 3 4 5 1 4 5 4 1 4 5 3 3 3 5 2 5 5 2 1 5 1 5 3 2 1 4 4 1 4 1 5 2 5 4 3
## [56845] 1 2 5 5 2 5 4 5 2 4 5 5 4 2 2 3 5 5 4 2 5 2 3 3 3 3 2 5 2 1 5 5 1 5 2 5
## [56881] 3 5 2 3 3 3 1 3 2 5 4 2 3 4 2 2 2 4 3 4 4 1 4 2 3 1 4 5 3 4 4 2 1 4 5 5
## [56917] 2 2 4 2 4 3 3 1 3 3 1 1 4 2 4 4 4 3 5 1 2 2 5 2 1 3 3 4 5 5 5 5 4 4 4 5
## [56953] 4 5 2 4 1 3 1 4 3 1 4 1 2 5 2 5 2 3 5 4 1 2 2 2 4 2 3 4 1 5 2 2 3 1 4 3
## [56989] 4 3 2 3 3 2 5 3 4 5 5 2 1 2 1 3 5 3 2 3 1 5 2 4 3 1 1 3 1 2 2 3 1 4 5 1
## [57025] 2 1 1 2 3 2 5 5 4 2 5 5 1 1 5 1 1 2 4 5 1 5 5 3 2 5 3 1 3 3 5 2 1 2 1 3
## [57061] 3 2 4 1 2 5 2 3 5 5 2 4 5 1 2 1 3 2 5 3 4 3 4 2 5 3 3 2 3 4 1 3 4 3 3 3
## [57097] 2 5 4 1 4 4 1 1 2 3 2 5 2 5 5 1 2 1 4 4 3 4 2 5 3 1 5 1 3 4 5 5 4 3 5 1
## [57133] 5 2 5 2 4 5 3 2 3 5 5 5 5 5 1 3 1 2 1 3 2 3 3 5 1 5 2 4 2 3 2 1 3 2 5 4
## [57169] 1 5 4 2 2 1 5 2 1 1 3 2 2 3 3 1 1 3 3 4 4 4 5 5 1 2 5 5 3 4 2 4 4 1 2 3
## [57205] 2 2 3 5 4 5 5 2 3 1 2 5 3 5 3 5 4 4 4 1 5 4 5 5 4 5 1 1 2 2 4 5 1 5 2 2
## [57241] 1 1 1 2 5 2 4 1 5 4 2 1 3 4 5 4 2 3 5 1 3 2 5 1 3 4 5 4 4 5 3 4 4 4 3 4
## [57277] 5 1 3 1 2 3 4 2 2 3 5 1 3 2 2 3 3 3 2 5 5 3 3 2 3 4 3 3 4 1 2 2 2 1 2 3
## [57313] 2 2 3 1 2 2 5 2 5 4 3 4 4 1 3 2 5 4 3 3 2 1 4 4 2 1 2 3 2 3 1 3 5 5 2 4
## [57349] 2 4 1 5 4 4 2 3 5 1 2 4 4 2 5 4 1 5 3 4 2 3 1 5 2 3 3 2 4 3 2 3 3 3 1 3
## [57385] 3 3 3 2 5 4 5 2 2 2 3 2 4 1 1 3 5 3 4 3 3 3 4 4 5 1 3 5 2 3 2 4 1 3 3 1
## [57421] 4 1 3 2 3 4 4 5 3 5 4 3 3 3 1 1 2 3 1 5 2 5 3 2 1 4 5 1 4 4 5 3 3 5 3 4
## [57457] 5 5 5 4 4 4 3 5 2 2 3 5 1 2 2 1 4 4 1 4 2 1 1 1 1 5 4 4 5 5 3 5 1 2 2 4
## [57493] 4 3 1 4 1 3 5 3 3 2 5 5 5 1 5 4 5 3 3 3 4 2 1 1 3 1 5 4 2 2 1 3 1 3 5 1
## [57529] 1 3 4 5 5 4 5 4 3 4 1 3 2 5 4 2 2 2 3 5 2 2 2 3 3 5 5 5 1 1 2 5 5 3 4 1
## [57565] 3 4 2 5 4 1 5 4 2 1 2 4 4 1 4 2 4 1 5 1 3 2 1 4 4 4 1 4 1 3 3 4 2 5 3 3
## [57601] 4 1 1 3 1 1 2 1 1 1 1 4 4 2 1 1 4 3 1 3 1 2 4 5 2 4 2 2 2 4 2 2 5 2 2 2
## [57637] 2 5 1 3 1 2 1 2 2 5 1 1 3 5 2 4 4 4 1 2 2 4 1 4 5 2 2 3 5 5 5 5 4 1 1 5
## [57673] 2 4 1 1 3 4 4 4 3 3 2 1 2 2 4 1 4 2 4 4 4 5 5 3 3 1 3 4 3 3 1 5 5 4 2 2
## [57709] 1 3 3 5 4 3 1 2 5 1 1 2 5 4 1 1 4 1 5 1 4 3 1 3 2 3 4 2 5 4 2 4 4 2 2 4
## [57745] 4 1 3 5 1 4 2 2 4 2 1 4 3 1 2 5 1 5 4 1 4 5 4 4 5 4 4 4 4 2 3 5 3 1 3 1
## [57781] 1 3 1 4 3 5 3 5 2 5 3 2 3 5 5 2 3 4 2 1 2 2 3 5 3 4 2 2 3 4 2 1 1 5 1 1
## [57817] 2 3 4 4 3 2 3 5 2 4 4 2 2 5 5 1 4 4 2 4 2 3 4 1 1 1 5 2 2 3 4 2 4 3 1 4
## [57853] 1 4 4 4 1 1 5 3 1 1 1 4 3 3 3 1 1 3 2 3 1 2 3 2 5 5 2 1 1 3 2 1 2 5 1 4
## [57889] 1 2 5 1 1 2 3 1 4 3 4 3 1 1 3 2 4 1 5 1 1 1 2 3 4 4 3 5 2 5 5 1 5 4 4 4
## [57925] 3 4 1 2 4 4 2 5 5 2 2 4 1 1 3 5 2 2 1 2 2 4 2 4 1 1 3 4 2 4 3 5 2 4 1 4
## [57961] 3 4 1 4 2 1 2 4 3 4 3 4 3 4 2 2 3 1 5 5 4 1 1 2 5 2 2 2 3 5 3 5 4 1 1 2
## [57997] 1 1 1 3 5 5 3 5 5 3 2 1 1 1 1 5 2 5 2 2 4 4 4 5 4 1 1 5 1 3 5 5 2 4 3 1
## [58033] 5 4 5 3 4 1 2 2 1 5 5 1 4 1 2 5 2 1 2 5 3 2 3 4 4 5 2 3 3 4 4 3 4 2 2 2
## [58069] 2 2 3 5 1 4 4 4 3 2 5 5 2 5 5 5 2 2 3 3 2 5 2 3 1 2 4 5 3 4 5 4 1 4 2 1
## [58105] 5 5 3 4 2 2 3 4 1 5 2 5 4 2 5 4 4 2 2 5 5 5 2 5 1 3 3 5 5 2 1 2 1 2 2 4
## [58141] 3 2 3 5 3 1 5 1 4 3 3 4 1 3 3 5 4 3 3 5 1 1 4 5 3 2 2 3 1 4 2 5 5 5 4 1
## [58177] 1 1 4 5 4 4 2 5 1 1 4 2 5 3 2 3 2 1 2 3 3 3 1 1 3 3 2 1 5 3 3 5 2 4 1 2
## [58213] 4 2 1 1 4 2 4 5 3 3 1 2 4 2 3 4 3 1 1 1 4 3 4 4 5 5 2 1 1 3 1 3 2 5 2 3
## [58249] 3 3 2 2 4 3 3 1 1 4 1 1 5 1 5 5 4 3 1 3 5 2 5 5 4 1 5 1 2 1 1 4 4 3 5 2
## [58285] 4 4 2 3 3 4 2 3 3 2 4 2 5 3 5 4 5 3 1 4 5 2 4 5 2 3 4 3 5 1 4 3 5 2 5 2
## [58321] 1 5 4 1 1 3 3 1 2 1 5 5 3 2 2 5 1 4 1 4 2 1 5 4 4 5 2 1 1 1 2 5 2 1 5 2
## [58357] 5 2 3 5 1 2 3 2 5 4 4 2 1 3 3 4 4 4 3 2 3 1 2 5 2 5 3 2 1 4 1 4 1 1 1 3
## [58393] 4 1 4 4 5 3 4 1 3 1 5 1 5 5 5 2 1 2 5 3 2 4 1 4 4 2 1 3 3 1 2 2 3 4 1 3
## [58429] 1 4 5 2 3 1 5 4 2 1 3 4 5 2 1 4 2 3 3 3 2 4 5 2 4 1 2 5 1 4 2 2 4 5 2 4
## [58465] 4 5 3 3 3 3 2 5 2 2 1 4 1 4 2 2 4 4 3 2 2 4 3 2 3 3 4 1 2 5 1 5 2 2 2 2
## [58501] 4 3 5 3 1 3 3 1 4 3 4 1 5 1 2 2 3 5 1 1 1 4 5 3 3 4 3 3 1 1 2 5 5 1 5 4
## [58537] 4 1 3 1 5 3 5 1 4 1 5 1 4 4 2 1 3 5 2 3 2 4 2 1 1 1 4 1 5 2 4 1 3 4 3 5
## [58573] 3 5 2 1 3 5 3 3 5 4 3 3 1 5 5 5 2 3 1 2 1 1 2 4 2 3 3 1 4 5 1 1 2 5 4 1
## [58609] 3 4 1 1 5 5 1 1 2 1 1 5 2 4 4 2 2 5 3 5 4 3 1 3 2 4 2 4 3 5 4 1 2 4 2 1
## [58645] 4 4 4 1 3 2 3 2 4 5 2 5 4 5 4 3 1 2 1 2 1 2 3 5 2 1 4 3 1 2 1 3 3 5 1 4
## [58681] 2 3 5 1 1 5 4 1 1 2 1 1 3 5 4 4 3 5 4 4 3 3 5 2 2 3 2 1 4 4 5 5 1 1 3 5
## [58717] 3 2 4 5 2 2 3 3 4 5 4 1 1 3 4 5 3 1 1 4 2 5 3 4 1 5 4 3 2 4 3 1 5 5 3 4
## [58753] 5 2 4 3 1 2 1 4 5 5 4 3 4 5 4 4 2 2 1 3 3 2 2 5 5 2 5 2 4 4 1 5 1 4 4 2
## [58789] 3 1 1 1 2 3 4 4 5 3 1 3 5 3 1 1 2 3 3 2 4 2 1 5 1 3 5 2 3 3 4 1 2 2 2 5
## [58825] 3 1 5 1 5 4 2 4 1 2 4 2 4 5 2 2 5 3 5 4 3 3 2 5 1 1 4 3 2 4 1 1 2 5 4 3
## [58861] 2 3 1 4 5 4 3 3 3 5 1 5 2 5 2 4 2 4 5 5 5 5 2 5 5 1 4 4 3 5 1 1 2 3 5 1
## [58897] 5 5 3 1 1 5 4 5 2 5 3 1 1 3 4 4 2 3 2 3 2 5 2 2 3 4 5 4 1 1 5 4 5 1 5 5
## [58933] 4 4 3 5 5 5 2 1 5 1 3 3 1 5 5 2 2 5 1 2 2 5 5 4 3 3 1 3 5 3 3 5 3 5 1 1
## [58969] 4 5 1 1 4 2 4 2 1 3 2 3 4 2 3 5 4 3 5 5 3 5 4 5 1 2 1 4 4 2 2 5 3 3 2 5
## [59005] 5 5 3 2 1 5 1 3 5 4 2 2 3 1 1 2 4 1 2 4 3 1 5 5 4 3 5 1 3 3 1 2 5 4 2 2
## [59041] 2 5 3 1 3 5 1 3 4 4 5 1 1 2 1 3 2 1 5 1 1 1 5 1 4 2 5 2 5 3 2 3 3 2 4 3
## [59077] 2 5 2 5 1 3 4 2 3 2 5 4 2 4 2 2 4 3 5 2 4 1 3 1 1 5 5 4 2 5 2 2 4 2 3 4
## [59113] 4 3 2 3 1 4 2 1 3 1 4 2 2 5 1 5 2 5 2 3 2 4 1 3 4 2 5 2 3 3 5 2 4 3 4 1
## [59149] 3 4 2 5 3 4 1 4 1 3 5 5 5 1 2 3 5 1 3 1 3 5 5 2 1 1 4 3 2 1 2 4 3 3 1 2
## [59185] 4 5 3 5 2 5 5 5 2 5 5 3 3 2 4 2 5 5 4 2 3 1 1 4 1 1 1 3 5 4 4 5 1 5 2 1
## [59221] 2 3 3 2 2 1 3 4 2 3 2 5 2 1 5 3 2 2 3 2 2 3 3 4 2 1 5 1 1 4 2 3 1 1 2 1
## [59257] 3 1 3 5 5 5 2 5 5 5 1 5 2 5 3 5 1 3 4 2 4 3 3 4 4 3 4 2 4 4 1 4 5 2 2 5
## [59293] 4 1 1 2 4 3 5 3 1 4 4 1 3 4 5 5 2 4 4 5 1 4 5 4 4 1 2 4 2 1 2 2 2 5 3 5
## [59329] 3 4 5 4 1 4 1 4 2 3 1 4 1 4 2 4 4 5 1 5 3 5 4 2 4 3 5 4 5 1 2 2 3 4 5 4
## [59365] 1 4 3 1 5 4 3 3 3 4 5 3 2 2 4 1 4 5 5 5 5 2 2 5 1 2 4 4 1 5 3 4 4 4 2 3
## [59401] 5 1 4 5 1 3 5 3 5 4 5 5 1 4 1 2 4 3 5 2 2 4 2 3 3 2 3 1 1 4 2 2 4 3 4 5
## [59437] 3 1 3 2 1 3 1 3 5 2 1 2 4 4 2 5 1 3 1 1 2 2 5 3 1 1 5 3 5 3 1 1 2 2 1 5
## [59473] 3 2 4 1 3 3 2 1 5 4 1 2 4 5 2 2 1 5 3 3 4 2 1 3 2 2 3 5 5 1 4 2 3 1 2 4
## [59509] 3 1 1 2 3 3 5 1 5 3 1 2 3 4 4 1 1 1 3 1 2 3 1 2 1 2 1 5 4 5 3 5 1 3 1 4
## [59545] 1 2 1 5 4 4 3 4 1 2 2 3 5 1 5 5 5 4 3 2 1 2 3 5 3 2 1 5 3 3 5 4 2 3 5 1
## [59581] 2 4 1 5 1 3 1 1 5 2 1 2 3 4 3 2 5 3 1 4 2 5 5 4 3 5 4 2 3 3 2 3 3 3 3 1
## [59617] 5 4 5 2 5 2 2 3 5 5 1 3 1 3 3 3 2 3 4 1 5 4 3 1 2 1 4 4 1 4 3 2 4 5 2 1
## [59653] 5 5 3 1 1 5 1 3 4 4 5 3 4 2 3 4 1 4 3 5 4 4 2 4 5 2 1 5 2 3 3 5 2 4 1 4
## [59689] 5 2 3 4 1 4 4 2 3 4 3 2 5 1 1 1 4 4 1 3 2 3 2 2 5 3 4 5 1 1 4 1 5 5 5 4
## [59725] 4 3 2 2 2 2 5 4 1 3 4 3 4 2 5 3 1 1 2 2 1 5 3 3 1 1 3 5 2 1 2 5 5 5 1 3
## [59761] 4 4 1 4 3 3 3 5 1 1 5 4 3 1 1 4 4 4 2 1 5 5 2 5 1 2 1 3 3 2 3 5 2 2 5 4
## [59797] 3 4 2 3 5 3 4 5 4 4 1 1 2 5 1 2 3 4 3 3 3 4 5 1 4 2 4 3 5 3 2 1 2 5 2 3
## [59833] 5 5 3 1 4 3 5 4 5 2 2 3 1 2 4 5 3 2 3 4 2 1 3 4 1 1 5 4 2 1 5 1 5 5 4 3
## [59869] 1 1 4 2 3 4 2 1 5 5 2 4 4 4 5 5 2 5 5 4 2 3 4 1 5 2 1 5 3 4 3 4 4 2 5 3
## [59905] 2 2 3 4 4 2 5 2 2 2 4 2 1 5 3 3 1 3 3 4 1 2 1 5 1 3 4 3 2 5 3 1 5 3 5 1
## [59941] 3 1 5 4 1 1 1 2 2 1 1 4 4 4 5 2 3 4 2 3 1 5 4 1 5 1 4 5 1 3 4 5 2 5 4 5
## [59977] 2 4 2 4 3 1 5 3 3 4 1 5 2 4 3 1 1 1 2 3 4 3 1 5 1 5 3 4 5 2 3 5 1 5 5 4
## [60013] 2 4 3 5 2 1 1 4 3 4 3 2 1 3 3 5 1 1 1 1 3 1 1 2 3 4 4 4 4 5 4 5 2 4 4 4
## [60049] 1 4 1 5 2 2 2 4 5 3 5 5 1 1 2 3 3 5 5 2 3 2 3 1 1 1 3 5 3 4 3 2 4 4 1 3
## [60085] 5 2 1 2 5 5 3 2 1 2 2 1 3 2 1 5 3 2 3 5 5 1 5 4 2 1 4 3 2 4 4 1 5 3 2 1
## [60121] 3 1 5 1 5 5 2 5 5 4 3 3 3 5 5 2 1 1 4 1 2 5 2 1 2 1 3 5 5 1 2 3 5 1 3 3
## [60157] 1 1 3 2 2 3 5 5 4 3 1 1 4 4 5 5 2 1 1 1 1 1 1 3 1 3 2 2 5 3 4 1 3 2 1 2
## [60193] 3 1 3 1 5 5 1 5 4 5 3 3 5 3 5 5 2 4 3 3 2 1 5 3 3 5 4 1 2 4 5 1 1 4 1 4
## [60229] 5 5 5 5 1 3 2 3 5 2 1 5 3 4 5 2 5 1 1 1 1 5 3 3 2 3 2 3 1 5 3 4 3 5 2 3
## [60265] 4 2 4 2 2 2 2 3 2 3 5 5 2 4 5 4 4 5 2 5 1 5 5 1 3 4 5 5 5 1 2 2 1 2 4 3
## [60301] 2 3 3 4 2 5 1 5 3 5 3 1 2 5 2 3 3 5 4 5 4 5 4 3 4 3 3 2 4 1 2 3 1 2 2 5
## [60337] 1 2 1 2 3 4 4 5 5 2 5 5 4 2 5 4 1 3 2 5 5 3 3 5 1 5 2 2 4 5 3 5 1 1 1 3
## [60373] 5 4 5 5 3 1 4 1 2 2 4 5 4 5 4 3 3 3 4 1 1 2 1 2 1 4 4 5 2 5 2 1 1 4 5 5
## [60409] 2 3 2 3 2 3 3 4 5 3 1 1 5 3 2 2 1 4 2 2 2 4 5 1 3 4 1 4 4 5 2 1 4 4 5 2
## [60445] 3 3 5 3 2 1 4 4 2 3 4 1 2 1 5 1 2 5 4 2 4 3 4 2 1 3 3 3 3 1 4 3 2 4 4 3
## [60481] 5 2 2 2 1 4 1 2 1 5 4 5 4 4 4 2 1 1 5 2 3 1 5 4 5 3 5 5 4 1 2 3 4 5 2 2
## [60517] 1 3 4 4 2 4 1 2 2 2 2 3 4 3 4 1 5 4 1 3 2 1 3 5 4 5 3 3 2 5 5 4 5 5 5 1
## [60553] 4 4 5 3 3 1 3 4 1 3 1 4 2 3 1 3 1 2 4 1 4 1 2 5 4 1 1 3 3 4 2 1 2 5 1 3
## [60589] 3 5 3 2 4 4 3 4 4 4 2 1 4 5 1 4 2 1 1 2 5 5 3 3 4 5 5 3 5 1 5 5 5 1 2 4
## [60625] 3 1 4 1 3 4 4 2 1 2 5 1 1 4 5 2 3 4 4 5 2 5 3 2 4 3 1 4 2 2 3 3 2 3 2 2
## [60661] 2 2 5 4 1 1 5 4 1 2 4 1 5 3 4 1 4 1 2 4 2 3 3 4 5 1 2 1 1 3 1 1 3 3 1 3
## [60697] 2 4 3 5 3 3 1 4 5 1 4 4 4 5 3 2 2 4 3 3 3 1 4 5 3 3 5 5 1 4 4 4 5 3 3 4
## [60733] 5 4 5 5 3 5 4 1 4 5 4 5 3 2 2 3 2 4 3 5 5 1 3 2 4 1 1 2 1 3 3 4 1 4 2 2
## [60769] 2 3 2 2 3 3 5 5 2 5 3 5 3 2 5 4 3 5 1 5 5 3 5 1 1 4 5 1 3 5 3 5 1 4 1 5
## [60805] 1 1 4 3 2 3 3 5 1 3 4 3 4 5 5 1 4 3 2 4 5 1 3 1 3 1 3 2 4 3 3 4 1 3 5 3
## [60841] 1 2 5 2 4 2 1 3 5 1 1 3 4 5 4 2 4 3 2 2 1 4 5 3 2 3 3 1 5 5 2 4 4 2 4 5
## [60877] 2 1 5 3 5 5 1 2 1 1 2 2 2 3 4 3 4 3 1 5 2 4 5 2 2 2 3 2 1 3 4 3 5 3 4 4
## [60913] 4 3 3 1 5 2 5 3 5 1 2 3 1 5 1 5 4 5 4 4 1 4 4 1 5 5 1 5 2 5 4 5 1 3 2 2
## [60949] 2 2 2 1 1 2 4 1 4 3 1 3 5 4 5 1 5 4 2 5 3 1 3 1 4 4 5 4 5 2 1 2 2 3 3 5
## [60985] 5 1 1 1 3 3 2 1 4 5 3 4 3 3 2 5 5 1 3 2 3 4 1 2 4 1 3 4 4 5 4 3 5 3 3 2
## [61021] 3 1 1 1 4 1 3 1 2 3 3 1 4 3 4 5 2 1 4 2 1 2 4 4 5 5 5 2 2 2 1 1 1 1 5 4
## [61057] 3 1 3 1 2 2 5 2 2 4 1 3 2 4 2 5 2 2 4 5 4 4 5 1 2 2 1 2 5 3 4 4 1 5 5 3
## [61093] 4 5 3 2 4 2 2 1 3 4 3 3 2 5 5 3 2 5 5 2 4 1 4 4 4 1 1 5 1 5 3 2 4 3 1 1
## [61129] 2 3 4 1 3 3 2 2 5 4 3 2 3 1 1 1 2 4 5 4 2 5 1 4 1 4 5 5 1 5 3 2 3 4 1 3
## [61165] 2 1 1 3 1 2 1 1 2 3 4 2 5 1 2 3 2 1 1 3 1 1 3 1 5 2 4 4 3 1 1 2 4 2 2 3
## [61201] 1 5 4 3 1 3 4 3 4 1 5 5 5 1 4 5 2 1 5 5 2 1 5 1 1 2 2 4 3 4 5 3 1 2 2 3
## [61237] 3 2 4 5 1 3 3 3 2 5 1 3 1 2 4 1 2 1 3 4 1 4 3 3 2 2 5 2 1 1 4 3 1 4 3 3
## [61273] 4 4 1 1 2 5 3 1 3 1 4 4 2 1 5 5 3 3 2 3 1 5 1 5 4 3 5 1 2 3 1 1 1 5 4 4
## [61309] 4 3 4 2 5 5 1 4 1 1 1 3 3 2 5 4 4 3 5 1 4 1 4 1 4 3 2 2 4 1 2 3 3 1 2 1
## [61345] 2 1 2 1 3 5 1 4 2 3 3 4 1 3 1 4 3 3 4 3 2 4 4 3 4 5 4 5 3 3 2 4 2 2 2 5
## [61381] 1 2 2 3 3 2 1 1 4 4 3 2 4 1 5 4 2 1 1 3 2 5 1 4 2 4 4 2 5 4 5 5 3 1 1 5
## [61417] 5 5 4 2 4 1 5 1 1 1 4 2 1 5 3 1 2 3 2 1 3 5 5 1 5 3 2 3 5 1 2 3 2 3 3 3
## [61453] 1 5 1 2 4 2 3 3 3 2 2 1 5 5 2 5 5 5 3 4 5 3 1 5 4 5 2 4 1 5 1 3 4 5 2 1
## [61489] 2 4 5 3 2 4 2 2 5 3 3 2 4 4 2 5 3 5 2 1 2 3 1 4 5 3 1 1 4 1 1 4 3 3 2 1
## [61525] 3 1 3 3 3 4 5 4 1 1 2 2 1 1 3 5 4 4 2 1 5 2 5 2 3 4 3 1 4 4 1 5 1 2 4 4
## [61561] 2 5 5 2 3 1 4 3 4 5 1 4 3 3 2 5 5 5 2 1 3 5 4 3 3 4 4 3 5 3 2 1 1 3 3 2
## [61597] 3 3 5 2 3 4 2 3 4 5 5 3 4 2 5 4 2 1 1 3 3 5 3 5 2 5 3 4 4 1 5 5 5 3 3 1
## [61633] 1 1 3 4 4 3 4 4 3 1 4 1 5 5 3 4 5 4 4 2 2 5 4 5 1 3 5 3 5 3 2 2 3 5 4 2
## [61669] 2 3 5 1 3 5 1 5 1 4 1 2 5 5 1 3 1 3 2 5 3 4 2 2 1 3 3 1 4 3 1 3 1 1 4 5
## [61705] 5 4 1 4 2 5 5 1 1 5 5 3 4 3 5 5 1 1 3 5 1 5 3 3 5 3 5 1 2 2 1 3 1 1 4 2
## [61741] 5 1 5 1 5 3 1 2 2 2 5 3 3 5 5 4 2 3 3 4 3 1 3 2 2 1 4 1 4 1 1 2 1 2 5 1
## [61777] 3 2 2 1 1 3 4 1 4 3 5 1 3 3 1 2 2 3 3 3 2 3 4 3 5 5 3 1 5 5 2 5 5 2 3 2
## [61813] 2 2 3 4 5 1 1 3 3 3 4 3 5 5 1 5 1 1 1 2 5 3 5 5 5 5 5 2 5 4 2 4 1 3 5 5
## [61849] 5 5 3 4 2 3 1 5 1 2 3 3 1 5 1 5 3 1 3 2 3 5 2 4 4 5 2 2 2 2 4 2 1 1 3 2
## [61885] 1 5 1 1 5 4 1 4 5 4 2 5 1 4 2 1 5 3 5 2 3 2 5 1 2 1 2 4 3 2 3 3 5 2 3 1
## [61921] 3 2 2 4 3 1 2 2 1 2 1 2 3 4 2 4 2 3 4 3 5 5 3 5 2 5 2 1 5 4 5 1 5 4 4 3
## [61957] 1 2 3 4 5 3 2 2 1 4 1 3 3 3 5 4 1 1 5 4 1 1 3 3 5 4 2 1 5 5 4 5 4 2 1 4
## [61993] 5 2 4 4 3 1 2 4 5 5 5 4 5 2 4 5 1 2 5 1 4 3 5 3 3 5 5 4 3 2 3 5 2 2 5 1
## [62029] 4 5 2 5 3 2 4 3 1 1 1 4 3 5 1 4 5 2 5 1 1 3 3 3 2 2 5 5 4 5 3 2 3 2 3 2
## [62065] 3 1 3 3 3 1 1 5 3 2 2 1 5 4 4 4 3 4 2 5 5 4 2 5 3 5 4 3 1 5 4 2 5 1 3 5
## [62101] 3 2 5 3 3 4 5 3 5 3 2 1 1 4 5 1 4 1 4 2 1 5 2 1 3 1 3 4 5 3 4 4 2 1 2 2
## [62137] 1 5 1 1 4 2 1 4 1 5 2 5 5 1 5 1 4 5 3 2 5 2 3 2 3 3 1 1 1 1 1 4 2 3 4 5
## [62173] 4 2 1 5 3 3 4 3 4 1 2 4 1 1 3 3 3 5 2 1 2 5 1 4 3 2 5 5 2 2 2 5 3 5 3 5
## [62209] 1 2 3 1 3 5 3 4 1 4 3 2 5 3 2 1 5 2 2 5 5 2 3 3 3 2 1 2 3 5 1 1 3 2 1 3
## [62245] 1 3 2 1 2 3 5 3 5 2 4 5 4 2 5 2 1 1 3 4 5 2 3 3 5 2 3 4 2 4 3 4 2 3 3 3
## [62281] 4 1 2 2 5 4 3 3 1 4 4 2 4 3 3 2 2 1 2 2 4 5 5 4 3 2 2 2 4 2 5 4 3 1 1 4
## [62317] 3 1 3 5 1 1 4 5 4 2 3 4 5 3 4 5 3 5 3 3 5 2 1 4 1 4 1 4 4 2 4 1 4 2 3 3
## [62353] 4 4 5 3 5 1 1 1 5 3 4 1 5 2 3 1 4 3 5 1 3 3 1 4 5 1 4 5 2 3 1 2 3 5 2 1
## [62389] 1 3 4 5 5 2 2 3 2 5 1 1 1 1 3 1 5 2 3 2 3 1 2 1 1 2 1 5 4 5 2 1 1 4 4 1
## [62425] 4 2 2 3 3 4 5 3 5 3 5 4 4 3 5 3 2 3 1 5 5 2 5 1 5 4 1 3 4 4 3 3 3 3 2 3
## [62461] 1 5 1 3 3 1 4 3 1 3 2 2 4 2 4 4 4 2 1 2 2 3 1 5 2 2 4 1 1 5 2 4 4 5 4 4
## [62497] 2 2 5 2 1 4 5 3 4 4 5 5 5 2 5 5 4 5 4 5 1 2 2 3 5 3 3 5 2 1 5 4 3 3 5 3
## [62533] 4 3 4 2 1 3 1 1 3 2 2 5 4 5 5 1 3 2 1 4 3 1 1 1 1 2 5 1 4 5 1 4 2 5 3 5
## [62569] 3 3 2 5 5 2 5 1 1 4 2 2 3 1 5 5 2 2 1 2 1 2 1 4 1 3 3 1 4 1 2 4 2 4 2 5
## [62605] 3 2 3 4 1 2 5 4 1 1 2 3 5 3 5 2 2 4 4 1 3 4 5 1 5 5 3 1 2 2 3 3 4 4 3 5
## [62641] 2 4 1 5 3 5 5 4 2 4 2 2 2 4 1 3 4 5 4 5 4 1 4 1 3 1 4 1 3 5 4 4 4 5 3 2
## [62677] 4 4 4 5 1 1 2 3 2 3 1 4 5 3 2 1 2 4 5 1 4 5 2 2 3 1 2 2 1 3 5 4 3 1 4 4
## [62713] 1 4 4 1 1 1 1 1 5 2 4 2 5 2 5 2 4 3 3 2 4 1 1 3 4 5 2 1 4 3 5 3 2 3 1 2
## [62749] 1 4 4 4 4 2 3 4 4 2 3 4 1 1 3 1 5 1 4 1 5 4 5 4 3 5 1 1 3 5 3 2 4 3 3 5
## [62785] 4 5 3 3 1 1 3 4 5 3 3 2 1 5 5 4 1 4 3 5 3 2 1 3 4 2 5 5 2 4 1 2 4 5 5 1
## [62821] 1 5 3 1 3 2 2 2 5 1 3 4 2 5 3 4 1 3 2 4 5 1 5 5 2 3 2 4 3 4 1 2 2 2 4 2
## [62857] 2 2 3 2 2 2 4 2 4 2 1 3 2 3 3 2 5 5 2 1 3 1 5 1 4 2 3 2 4 1 2 5 1 4 3 5
## [62893] 3 4 5 4 1 2 2 4 3 4 4 1 4 1 4 1 1 3 5 5 4 5 3 2 3 5 5 3 4 3 5 3 4 3 1 5
## [62929] 1 4 5 3 3 5 1 1 4 2 1 3 5 4 4 1 5 1 3 5 3 4 4 1 5 5 5 5 3 1 4 3 5 4 2 3
## [62965] 2 3 1 2 1 1 5 2 3 4 4 2 1 5 5 2 1 4 1 1 4 2 3 5 2 4 4 1 2 2 1 5 2 3 5 5
## [63001] 5 2 4 5 1 4 1 3 4 1 5 5 1 1 2 4 2 2 5 2 5 5 2 5 3 5 2 4 2 3 4 4 1 1 4 5
## [63037] 5 1 3 3 1 5 4 1 2 5 5 2 1 5 3 5 2 3 5 4 1 4 2 1 4 1 4 2 5 4 1 1 2 5 3 3
## [63073] 3 3 4 4 2 5 1 4 4 2 1 3 4 1 5 1 4 3 2 2 5 3 2 5 5 4 2 4 3 1 2 2 4 5 3 1
## [63109] 3 2 3 1 1 4 2 2 3 5 4 5 2 1 5 1 3 1 2 5 5 5 5 2 1 4 3 3 4 4 3 3 3 3 1 4
## [63145] 2 1 1 5 5 1 3 1 5 4 4 3 4 2 2 1 5 1 3 4 1 5 3 4 5 4 5 3 5 4 5 1 2 5 1 2
## [63181] 1 5 4 2 1 1 1 1 5 1 3 5 3 2 5 1 5 2 3 2 4 4 2 1 4 5 4 2 2 5 1 5 4 1 1 2
## [63217] 2 1 4 3 4 4 1 3 4 3 4 4 1 1 5 5 2 2 4 1 3 3 3 4 5 2 3 1 4 3 4 3 2 5 2 4
## [63253] 5 5 1 3 1 1 3 2 5 2 3 2 4 1 1 4 1 4 2 2 1 2 3 3 3 1 3 4 2 5 1 2 5 5 2 4
## [63289] 2 5 3 5 2 1 4 1 2 4 1 5 2 4 3 2 1 1 2 5 2 4 5 5 3 4 4 1 5 2 5 5 2 5 4 3
## [63325] 4 2 1 4 3 5 5 4 4 3 5 2 3 1 1 3 1 3 5 1 2 5 5 4 3 5 3 5 4 2 3 5 3 4 2 4
## [63361] 4 5 4 2 4 3 4 4 2 5 4 5 5 3 2 4 5 1 4 5 3 5 4 4 1 4 1 5 2 3 4 3 4 2 3 2
## [63397] 3 5 5 4 4 2 1 1 2 4 5 1 2 2 3 2 3 3 3 1 5 5 5 2 2 5 1 5 5 4 1 2 4 5 5 2
## [63433] 2 2 5 5 1 2 3 4 1 4 2 1 3 3 1 3 3 5 3 3 5 2 2 5 4 1 3 1 4 3 1 5 2 4 2 3
## [63469] 2 4 1 2 2 3 2 1 1 5 3 3 3 5 4 4 4 1 3 5 4 4 2 5 5 2 5 1 3 4 2 4 2 4 3 2
## [63505] 3 1 3 4 3 1 2 3 3 5 1 2 3 3 3 4 4 4 4 5 3 2 5 5 3 1 2 4 4 5 3 1 3 4 3 5
## [63541] 1 4 2 4 3 4 5 4 3 1 1 1 1 2 2 5 5 1 4 4 5 3 1 3 1 2 1 1 4 3 2 1 4 5 1 2
## [63577] 1 5 2 1 3 2 4 3 3 2 5 2 3 2 2 4 5 4 1 2 5 4 5 2 1 5 4 4 4 2 3 4 3 5 2 5
## [63613] 4 5 2 1 3 5 2 2 4 5 1 2 3 1 1 5 1 3 2 2 2 5 1 2 1 5 2 4 5 5 1 1 5 3 5 1
## [63649] 3 1 4 5 1 1 4 4 3 5 5 5 4 2 2 2 1 1 1 2 2 5 5 5 1 5 2 1 4 4 5 3 5 3 1 4
## [63685] 5 1 1 3 4 5 3 2 4 2 5 4 1 1 3 5 5 3 2 2 2 1 1 2 3 4 1 5 3 5 5 2 3 2 3 2
## [63721] 4 4 4 2 2 3 3 4 1 2 4 3 3 3 3 3 2 5 4 3 2 1 1 2 2 2 1 4 5 3 1 2 4 3 4 2
## [63757] 3 1 2 4 2 1 2 4 3 5 2 5 2 4 4 3 5 5 3 1 5 2 2 2 5 4 2 4 3 3 2 2 2 1 1 5
## [63793] 4 2 5 1 5 5 5 5 1 1 5 3 4 4 5 5 5 5 4 5 3 4 2 4 2 1 3 4 1 4 5 3 4 3 5 3
## [63829] 3 3 3 2 1 4 1 5 5 4 2 2 4 3 2 5 4 2 4 4 5 5 1 5 5 5 4 5 3 4 5 5 4 2 3 2
## [63865] 1 2 3 3 1 1 2 3 2 4 2 5 2 3 2 1 5 3 3 2 2 5 3 1 5 5 3 1 1 4 2 5 5 3 3 5
## [63901] 1 3 4 1 3 1 5 3 4 3 4 3 3 2 2 3 5 4 2 2 2 3 3 2 4 2 2 1 1 4 3 1 2 1 4 1
## [63937] 1 2 4 4 4 4 5 5 4 1 1 2 2 4 4 4 2 5 5 1 2 3 1 2 1 2 5 4 5 4 1 2 4 2 1 4
## [63973] 5 1 5 5 4 4 2 1 4 4 5 1 1 1 2 2 5 1 1 4 1 3 4 2 4 2 3 4 3 1 4 3 3 5 3 4
## [64009] 5 5 5 2 5 2 5 4 4 1 5 5 1 2 4 1 4 1 4 5 1 1 5 5 3 5 1 2 2 3 4 3 3 2 1 5
## [64045] 1 4 1 1 5 5 1 3 1 5 5 4 3 5 5 1 3 5 2 1 4 1 2 5 1 3 3 2 2 5 2 4 4 5 5 4
## [64081] 5 3 5 3 4 1 1 4 2 1 2 3 2 5 2 2 2 3 2 3 1 1 4 4 2 3 3 4 1 5 5 4 1 1 5 1
## [64117] 5 1 3 5 1 1 1 5 4 5 2 1 1 3 1 3 2 3 1 3 1 3 1 1 1 3 2 2 5 1 5 4 1 5 3 5
## [64153] 5 1 3 3 2 5 5 1 5 2 3 5 1 1 4 5 2 5 3 2 1 2 3 3 1 4 5 2 1 5 3 1 1 2 3 4
## [64189] 2 2 1 1 3 5 4 3 2 5 5 3 5 1 3 4 3 1 3 4 3 2 3 5 2 2 3 3 4 1 3 2 1 4 5 2
## [64225] 1 1 2 3 1 3 4 2 1 4 3 5 5 1 2 4 3 2 3 5 3 5 5 5 5 5 3 5 1 2 1 5 4 4 2 1
## [64261] 1 2 4 1 4 3 5 5 3 3 4 5 3 3 1 3 5 1 1 3 5 5 1 5 3 2 4 4 3 1 3 5 4 4 4 5
## [64297] 4 3 3 1 3 1 4 4 4 3 2 1 3 3 5 2 3 4 4 3 1 5 3 2 4 5 4 4 3 4 3 2 2 5 3 4
## [64333] 4 2 3 5 5 3 5 5 3 2 5 2 1 4 1 1 5 5 3 5 5 3 2 3 4 4 5 2 2 2 3 5 1 5 1 1
## [64369] 5 3 2 3 5 2 4 4 3 2 4 4 1 2 5 1 2 1 3 3 1 2 2 3 5 5 3 3 5 4 2 4 2 3 1 5
## [64405] 3 5 1 2 5 1 3 2 3 5 5 2 1 3 1 1 5 4 2 3 1 2 5 2 1 4 2 2 1 3 3 5 2 1 3 5
## [64441] 3 2 5 5 1 4 3 1 2 2 5 3 2 1 4 2 5 3 2 3 4 5 1 2 5 1 4 5 1 4 1 1 4 4 1 2
## [64477] 2 1 3 2 4 5 5 2 3 3 4 1 3 1 1 5 2 1 2 4 1 5 4 5 5 2 2 1 2 2 4 5 4 4 4 1
## [64513] 3 4 2 4 3 3 5 3 3 1 4 3 2 2 2 2 1 3 2 4 5 5 1 5 4 1 5 3 5 4 2 2 1 4 4 3
## [64549] 2 2 5 4 1 3 4 5 5 2 1 4 2 3 4 5 3 2 1 3 2 1 1 3 1 2 1 4 3 1 4 4 3 3 2 2
## [64585] 2 5 4 5 4 5 5 4 4 1 1 1 2 3 4 2 4 2 5 5 1 3 2 3 3 3 1 2 2 5 5 5 4 5 5 4
## [64621] 3 4 5 2 5 4 3 3 5 2 4 3 3 1 2 5 4 2 4 4 4 1 2 5 1 4 5 2 2 2 5 4 4 1 2 5
## [64657] 5 3 2 4 2 1 4 4 4 2 3 4 1 1 1 3 3 4 2 5 4 1 1 3 4 5 4 5 2 4 2 1 2 1 5 2
## [64693] 2 1 5 4 1 4 2 3 4 1 2 2 3 3 2 2 3 4 2 1 3 2 1 3 3 4 3 3 4 1 3 1 1 2 2 3
## [64729] 3 2 5 4 4 4 3 2 1 3 4 5 4 2 4 4 1 4 3 5 2 2 1 3 1 4 5 5 5 2 3 2 1 1 1 5
## [64765] 2 1 3 2 4 2 1 4 4 1 2 2 2 3 5 2 1 1 3 3 3 1 5 1 1 5 1 2 4 3 4 5 1 5 4 3
## [64801] 1 3 4 2 2 1 3 4 4 3 1 3 2 2 3 3 1 1 1 2 1 3 2 3 4 1 4 4 1 5 4 3 4 3 4 4
## [64837] 4 1 2 1 3 4 3 4 5 2 5 4 2 1 3 1 3 5 1 5 4 5 4 2 3 4 5 5 3 3 1 4 5 3 4 1
## [64873] 1 2 1 2 1 4 2 5 4 4 3 1 3 1 5 4 4 2 3 4 3 4 2 2 4 4 3 4 3 1 2 1 2 1 2 1
## [64909] 5 5 5 5 1 1 5 1 1 5 4 4 5 4 3 2 3 5 1 4 2 3 3 3 1 1 2 3 1 4 1 1 5 1 2 1
## [64945] 1 3 1 3 2 5 4 2 5 2 4 5 2 1 4 2 5 4 5 1 5 3 5 5 2 3 2 3 5 1 4 1 1 3 2 3
## [64981] 3 1 4 3 5 3 4 5 2 1 3 2 3 2 1 5 1 2 4 1 4 2 1 1 1 2 3 4 5 4 5 3 2 5 2 1
## [65017] 3 5 5 5 1 5 4 5 1 2 1 2 4 2 5 1 5 5 5 3 1 1 5 1 3 4 5 5 2 4 3 2 4 1 1 5
## [65053] 2 1 3 3 1 5 2 4 1 5 4 5 1 3 4 5 2 5 5 4 1 3 3 5 3 4 3 4 4 5 5 2 4 4 1 1
## [65089] 5 5 4 4 2 1 3 4 1 2 1 1 2 2 2 3 2 1 1 4 1 2 2 1 2 1 3 5 2 4 2 4 2 1 4 5
## [65125] 2 3 1 4 3 3 5 4 3 5 3 3 4 4 1 4 5 3 1 4 1 2 4 4 3 3 4 4 5 3 2 2 5 3 4 3
## [65161] 2 3 4 1 1 5 2 2 3 5 4 5 3 3 1 5 1 5 5 3 1 1 2 1 1 3 1 4 4 5 4 3 3 1 2 2
## [65197] 1 2 4 5 5 3 4 3 4 3 5 5 3 5 1 5 1 1 2 4 3 2 1 2 5 2 3 1 3 3 4 2 4 2 1 2
## [65233] 4 3 4 5 4 5 4 2 2 2 4 1 3 5 1 1 4 3 1 2 5 5 5 1 5 1 1 4 5 5 4 1 3 1 4 5
## [65269] 5 4 1 1 4 5 1 1 2 4 5 4 2 5 2 5 5 1 4 3 4 1 3 1 3 5 5 4 3 2 4 2 5 3 5 5
## [65305] 3 5 2 5 5 3 3 2 5 5 1 5 2 4 5 5 4 3 2 1 4 4 2 1 5 5 3 2 3 5 5 4 3 3 5 2
## [65341] 1 1 1 3 4 1 2 2 3 3 3 3 4 4 1 5 1 3 2 5 1 3 5 2 3 1 5 5 2 2 4 3 2 5 1 5
## [65377] 3 1 2 4 1 5 5 3 3 4 1 3 3 3 5 4 5 4 4 4 4 2 4 1 3 2 2 4 3 5 4 2 5 2 4 2
## [65413] 3 1 2 5 5 1 2 3 1 4 1 2 3 5 4 5 5 3 5 4 5 4 3 5 1 5 2 2 5 4 1 4 3 1 1 2
## [65449] 4 5 5 4 3 1 2 1 1 3 5 4 2 5 1 3 2 2 3 1 3 3 3 1 1 3 3 5 1 4 3 4 4 2 3 5
## [65485] 1 4 5 5 3 3 3 4 3 3 5 3 3 2 1 4 2 2 1 5 1 1 2 2 4 4 5 2 3 2 3 5 4 2 1 4
## [65521] 5 2 1 1 5 2 4 2 3 5 2 3 1 4 5 1 3 2 4 2 4 4 5 5 5 5 5 1 3 2 2 2 4 3 1 1
## [65557] 1 3 1 5 3 5 4 2 1 1 4 4 1 4 5 3 5 4 1 4 1 3 5 5 1 5 4 1 3 3 5 2 4 2 3 3
## [65593] 1 2 4 4 5 3 5 3 3 1 2 1 5 4 5 5 2 5 4 1 2 1 2 1 1 1 1 1 2 3 1 1 5 4 5 2
## [65629] 3 3 5 1 2 2 2 5 2 1 3 1 4 5 4 3 4 4 5 1 4 4 3 5 3 5 3 5 2 1 2 2 3 3 4 1
## [65665] 4 2 5 1 5 2 4 5 5 4 1 4 2 2 1 3 1 3 5 3 4 3 4 2 4 3 2 4 4 3 1 5 1 3 3 1
## [65701] 4 1 1 4 4 4 5 3 4 2 3 1 2 4 1 3 1 2 1 1 2 4 2 2 5 4 1 5 5 4 2 1 1 5 4 3
## [65737] 3 2 4 5 5 3 3 5 3 4 2 4 2 4 2 4 5 4 1 3 3 3 2 3 5 4 4 3 5 2 5 4 4 5 1 4
## [65773] 1 3 1 3 1 2 1 2 5 4 4 1 2 2 2 5 2 3 1 5 1 3 5 3 3 1 5 3 4 4 2 1 5 1 1 2
## [65809] 4 5 5 4 2 4 3 5 4 1 2 4 1 3 1 4 3 3 1 4 2 5 3 4 4 2 2 3 2 5 1 5 5 1 5 5
## [65845] 1 5 1 5 5 5 3 1 1 2 5 2 4 1 3 3 3 3 1 5 4 2 3 5 3 1 1 3 4 5 3 4 3 1 2 2
## [65881] 2 1 1 5 4 5 5 3 1 1 3 5 5 3 1 2 5 3 4 2 1 3 5 4 3 2 1 1 5 4 4 2 2 2 5 5
## [65917] 4 5 3 1 1 4 4 5 4 3 4 3 3 5 4 2 1 4 5 2 4 4 1 4 1 3 1 5 3 2 2 4 3 1 3 2
## [65953] 4 5 5 4 5 5 2 5 1 4 4 1 2 5 1 4 1 2 4 1 1 1 2 4 2 3 2 4 2 3 2 2 1 4 2 5
## [65989] 4 5 2 1 4 2 1 2 1 3 1 5 5 4 5 1 4 2 1 3 2 1 3 1 5 1 2 5 1 4 1 3 1 1 4 2
## [66025] 3 4 5 1 5 3 3 1 2 1 3 3 2 4 2 4 4 2 1 2 5 5 2 1 1 3 5 3 1 2 2 4 2 3 3 5
## [66061] 2 5 5 5 5 1 2 5 3 4 2 3 4 2 5 4 5 5 3 3 1 5 4 5 4 4 3 5 5 4 3 2 2 2 1 5
## [66097] 4 5 1 1 5 2 2 4 1 3 1 2 3 2 3 4 4 5 5 2 2 3 3 3 4 1 5 2 3 5 1 5 1 1 4 4
## [66133] 3 2 4 3 1 3 1 1 3 5 5 1 1 1 3 5 4 4 4 5 5 4 5 5 3 1 3 4 5 4 4 2 5 4 2 4
## [66169] 3 4 2 2 1 2 1 5 4 5 3 1 5 5 1 4 2 1 5 1 2 2 4 3 4 3 4 5 4 5 3 4 4 4 2 4
## [66205] 2 1 3 4 1 5 2 1 3 3 2 2 4 1 4 2 1 4 5 3 1 1 3 1 5 4 3 3 2 2 1 3 1 1 3 3
## [66241] 3 1 2 2 5 3 3 2 4 4 3 5 3 4 1 5 4 5 4 2 1 4 3 3 3 2 4 3 2 2 5 2 2 4 3 5
## [66277] 3 5 4 3 1 5 3 2 2 3 2 5 5 1 1 1 5 5 1 5 1 3 4 1 3 2 3 4 4 1 4 1 4 1 2 5
## [66313] 2 3 2 5 3 2 5 4 3 5 2 1 1 5 5 2 2 5 5 4 1 5 3 3 1 1 3 1 3 2 3 3 3 4 3 5
## [66349] 5 5 5 2 4 4 4 4 1 5 1 3 4 4 1 5 1 5 3 1 4 4 1 2 1 1 3 1 3 2 2 3 1 2 3 2
## [66385] 4 4 1 1 4 4 4 3 2 3 1 5 4 1 4 3 3 4 5 2 4 2 4 1 4 5 5 2 4 1 2 1 1 2 5 1
## [66421] 5 4 1 4 3 1 4 2 4 3 3 3 5 1 3 2 5 3 4 4 1 1 2 1 2 2 3 5 2 2 4 4 2 2 3 3
## [66457] 5 2 2 4 1 3 3 5 2 2 1 2 4 3 5 1 3 3 4 1 2 2 1 1 3 2 1 5 4 1 5 4 3 5 2 4
## [66493] 4 3 5 1 3 3 2 1 2 2 5 4 3 3 5 2 1 2 4 5 5 4 4 4 1 3 2 1 3 4 4 4 5 3 4 3
## [66529] 4 1 3 1 4 3 3 3 4 1 5 5 5 1 5 3 1 2 3 4 5 2 5 1 5 1 2 3 4 5 1 2 5 3 3 3
## [66565] 4 2 2 5 2 2 4 5 5 3 3 5 3 1 2 4 2 2 3 3 3 4 4 1 5 2 1 5 3 5 1 5 2 1 2 1
## [66601] 5 3 4 1 2 4 1 1 2 2 1 1 5 2 4 1 5 1 2 3 5 5 2 5 3 4 3 3 2 4 5 4 3 2 1 3
## [66637] 4 5 4 2 4 3 3 1 1 1 1 4 4 5 5 1 5 2 5 4 2 3 3 5 3 3 4 2 5 1 5 4 3 4 3 4
## [66673] 3 3 3 1 3 3 5 3 4 3 4 3 3 2 1 5 3 5 5 2 3 1 3 3 4 2 1 2 4 4 1 4 3 2 5 2
## [66709] 5 4 4 1 1 1 4 4 3 1 5 1 4 2 2 5 3 2 5 4 2 4 4 2 4 4 5 1 4 5 4 3 4 5 5 3
## [66745] 4 2 4 4 4 5 5 2 2 2 2 5 4 1 3 5 1 4 5 5 2 1 1 5 2 3 5 4 2 3 4 4 3 4 5 5
## [66781] 2 4 2 2 4 3 3 4 1 4 3 2 2 5 4 2 1 4 3 4 1 3 2 1 2 2 2 5 5 4 1 4 3 5 1 5
## [66817] 2 3 4 2 5 4 1 2 2 3 3 2 4 4 4 1 1 1 3 4 4 4 1 2 4 2 1 3 1 5 4 2 1 1 2 2
## [66853] 3 4 1 4 3 3 3 2 2 4 3 4 4 4 5 1 2 2 4 3 1 3 1 1 3 4 4 3 1 2 3 1 5 5 3 4
## [66889] 5 2 4 5 5 5 5 4 5 4 5 5 1 1 3 4 3 5 2 3 5 4 5 5 2 5 4 1 5 5 5 2 3 3 4 4
## [66925] 3 1 1 5 3 2 3 1 1 3 2 2 3 4 4 4 2 3 4 4 1 3 3 1 1 2 3 3 1 3 1 3 3 1 4 4
## [66961] 2 3 5 2 2 2 4 3 5 2 3 1 1 5 2 5 1 1 1 4 3 2 5 1 3 5 5 2 4 3 5 3 3 3 1 4
## [66997] 3 2 5 3 4 3 1 5 1 2 3 3 2 4 1 4 4 5 3 5 5 2 4 4 2 1 4 3 2 3 3 1 5 4 1 1
## [67033] 1 2 2 5 5 3 1 1 2 1 5 1 1 2 5 5 3 1 2 3 1 3 4 1 3 3 4 3 5 2 1 2 2 4 4 4
## [67069] 2 1 3 3 3 1 5 2 4 2 2 3 3 4 2 2 1 4 3 2 5 3 3 3 4 4 3 3 5 2 3 2 5 4 3 4
## [67105] 1 4 2 5 3 5 2 5 5 3 1 4 5 3 4 2 1 2 5 4 5 4 1 5 4 5 4 1 5 1 3 5 4 4 3 5
## [67141] 1 3 2 1 3 3 5 1 3 4 2 1 2 1 2 2 3 4 3 2 5 3 4 2 2 4 5 1 4 4 2 4 2 1 5 4
## [67177] 1 4 5 5 5 4 2 3 3 4 1 5 2 4 4 3 5 2 3 4 5 4 4 3 2 5 2 4 2 4 5 4 4 4 5 5
## [67213] 3 1 4 3 4 5 2 3 3 2 3 1 5 1 3 1 4 2 1 2 5 4 5 3 4 3 2 4 2 2 3 3 1 4 2 3
## [67249] 4 4 4 2 3 1 3 4 1 1 4 1 4 3 4 5 3 5 3 3 2 4 2 1 3 2 5 4 1 2 3 2 4 2 2 4
## [67285] 3 3 3 5 4 4 5 2 2 2 2 1 4 2 4 5 2 4 2 1 4 5 2 1 5 3 1 4 5 2 2 5 4 3 4 1
## [67321] 1 4 5 5 2 5 5 3 2 5 3 4 3 2 1 1 3 5 5 2 5 1 3 5 5 2 4 2 2 5 2 4 5 4 5 4
## [67357] 5 3 5 1 4 2 1 3 2 2 3 4 5 1 3 1 4 3 5 1 2 3 4 3 3 3 5 5 4 5 2 5 3 3 1 4
## [67393] 3 1 2 5 5 1 2 2 3 4 5 1 4 2 4 4 4 5 2 4 3 1 1 5 3 2 3 5 3 4 2 2 4 4 3 4
## [67429] 4 1 1 3 2 1 5 3 1 2 1 4 2 4 4 2 1 1 3 2 5 1 2 5 5 5 1 4 1 4 5 4 3 3 3 1
## [67465] 1 5 3 3 5 4 4 3 4 4 3 3 4 3 4 3 4 1 1 5 2 2 3 2 1 4 2 2 2 2 4 3 4 2 1 5
## [67501] 1 3 3 2 1 5 1 1 2 1 4 3 2 2 2 5 4 5 1 5 1 1 4 5 3 5 3 5 3 2 3 4 5 5 1 5
## [67537] 3 1 1 4 3 5 3 4 4 1 4 5 3 1 4 5 5 4 3 4 2 5 1 1 3 1 1 2 4 5 3 2 1 2 3 1
## [67573] 1 3 2 5 5 3 2 1 4 5 2 4 2 3 1 4 3 1 3 4 3 4 5 1 3 2 3 2 3 2 1 5 2 4 2 1
## [67609] 2 3 3 2 2 5 4 3 1 5 2 2 2 5 2 2 1 1 5 2 2 2 1 2 1 4 1 3 4 3 5 1 5 5 2 4
## [67645] 4 1 3 4 4 5 4 2 1 1 5 4 4 3 5 4 3 2 5 3 5 2 3 3 3 4 5 2 2 4 5 2 2 2 1 2
## [67681] 3 5 4 4 4 5 5 5 1 5 4 4 3 3 2 2 5 5 5 1 5 1 2 4 3 1 3 2 5 3 4 2 5 2 4 4
## [67717] 3 2 2 3 2 3 1 3 4 3 4 5 2 3 4 2 4 4 1 2 3 2 3 1 2 2 3 4 4 3 4 4 2 4 5 5
## [67753] 1 2 3 4 5 5 5 1 2 4 3 3 1 4 4 3 2 5 1 4 3 4 5 1 3 1 4 5 5 1 3 2 2 5 5 3
## [67789] 5 1 5 4 5 2 3 4 5 1 3 3 5 5 1 4 2 4 1 2 1 1 1 3 4 2 3 3 3 4 5 5 5 2 3 4
## [67825] 3 3 4 1 1 1 1 1 2 3 2 1 2 5 4 5 1 4 2 1 2 5 2 2 3 3 5 2 5 3 5 5 1 3 3 3
## [67861] 4 2 2 2 5 1 2 1 5 4 1 3 4 2 4 2 4 4 3 1 4 3 4 5 4 5 5 1 3 2 4 1 2 3 2 5
## [67897] 5 2 5 2 3 3 2 4 2 3 5 2 5 5 2 2 4 4 3 2 3 2 4 1 1 3 2 4 4 5 5 5 3 2 4 4
## [67933] 5 4 2 1 4 2 2 1 4 2 2 3 4 1 2 5 5 1 5 2 1 4 2 5 3 5 3 5 2 1 4 5 1 3 2 4
## [67969] 1 2 5 1 3 4 1 3 4 4 3 4 3 1 1 4 5 3 4 5 4 3 3 1 2 2 4 5 4 3 5 3 3 3 1 4
## [68005] 2 5 4 3 3 1 5 3 4 2 3 4 1 2 3 1 2 1 2 4 5 3 5 3 3 2 1 4 3 4 5 1 5 3 2 5
## [68041] 4 2 4 5 2 2 2 5 5 3 2 1 1 5 5 3 3 5 4 1 5 4 4 5 2 4 1 4 2 4 3 4 2 5 3 1
## [68077] 3 1 4 2 1 3 3 4 5 2 2 2 5 3 2 4 1 5 1 5 2 3 4 2 1 4 4 5 2 3 3 5 4 1 5 5
## [68113] 1 1 5 5 4 3 1 3 2 1 2 4 1 5 4 4 4 2 1 2 2 4 3 2 5 5 5 1 1 1 2 2 3 2 2 5
## [68149] 1 3 4 3 5 4 5 5 2 3 3 2 1 5 4 1 5 5 1 5 4 1 1 1 2 1 5 3 3 1 1 2 1 1 2 2
## [68185] 4 1 1 3 5 1 1 1 3 3 4 4 1 2 5 4 2 1 4 4 3 3 4 1 3 2 2 3 2 4 5 3 2 1 5 4
## [68221] 5 1 3 5 5 3 4 3 2 1 5 2 4 2 4 1 1 3 1 4 5 2 5 4 2 2 5 2 1 5 2 1 1 5 1 4
## [68257] 4 4 3 5 3 2 4 3 1 5 4 1 1 4 4 3 4 3 1 5 2 3 1 1 5 2 4 3 1 2 1 4 1 4 5 1
## [68293] 4 3 5 5 5 1 2 4 3 3 3 3 5 5 2 2 5 4 4 1 2 1 2 1 5 4 5 3 5 5 2 2 5 1 2 5
## [68329] 2 4 5 2 2 3 2 4 1 1 3 5 3 4 5 5 3 5 3 2 5 2 4 2 5 4 3 1 4 3 1 5 2 2 3 5
## [68365] 1 2 2 1 5 2 5 5 1 2 1 3 3 5 2 3 4 4 2 1 2 1 5 1 2 5 3 1 1 3 3 3 4 4 4 3
## [68401] 4 5 2 2 4 2 1 4 2 1 1 4 1 1 4 4 5 2 2 2 2 3 3 4 1 3 3 3 1 1 5 4 3 3 2 3
## [68437] 2 3 4 5 1 4 5 4 3 3 2 1 2 5 4 1 4 4 3 2 5 3 5 4 1 2 2 4 4 3 3 5 4 3 5 5
## [68473] 5 4 1 3 4 4 5 5 3 5 5 3 4 2 4 2 5 4 1 4 3 1 3 5 3 2 3 4 2 1 4 3 4 3 3 3
## [68509] 3 2 1 1 3 5 5 5 5 4 2 3 5 5 2 2 1 5 1 5 2 2 4 5 3 2 1 4 5 5 1 4 3 3 4 1
## [68545] 2 2 2 2 4 1 3 5 4 1 1 3 1 2 4 3 2 2 3 4 3 4 2 4 1 5 4 4 5 5 2 3 1 5 3 1
## [68581] 1 2 3 1 5 2 4 3 4 1 4 5 3 1 2 2 4 5 5 3 3 1 5 4 1 1 2 4 3 4 2 5 5 4 2 3
## [68617] 1 2 4 4 2 2 5 1 4 4 5 5 2 1 3 1 4 2 2 5 3 1 4 4 2 2 4 1 4 2 2 3 4 4 5 1
## [68653] 4 3 1 2 3 5 2 2 2 2 4 5 3 1 2 2 4 1 5 1 3 3 2 3 2 3 3 1 3 5 4 4 5 1 1 5
## [68689] 2 3 4 3 4 2 1 4 5 2 5 2 4 5 3 1 3 3 1 1 4 4 3 5 4 4 1 4 1 3 1 1 4 5 3 3
## [68725] 4 2 4 1 5 3 2 1 4 2 1 4 3 4 4 2 5 3 3 1 4 4 2 2 1 2 3 5 5 3 4 5 3 2 2 5
## [68761] 5 5 3 3 2 3 4 1 2 3 5 1 2 3 1 5 4 1 5 2 5 3 4 3 4 4 3 2 4 4 2 3 1 4 1 5
## [68797] 4 4 4 5 4 2 3 5 5 2 5 1 1 2 5 4 4 3 4 4 4 4 5 4 5 2 5 5 3 3 4 3 4 4 3 5
## [68833] 5 2 4 1 3 5 3 4 3 2 1 1 1 3 5 4 5 1 3 4 4 2 3 4 2 2 4 4 5 2 2 1 5 2 3 1
## [68869] 1 4 3 5 2 1 2 1 5 5 4 2 3 1 3 5 1 4 3 2 3 1 4 4 4 2 5 4 2 4 4 3 4 5 3 5
## [68905] 2 3 1 3 5 1 2 2 2 1 3 2 4 4 3 4 4 1 1 4 3 5 2 5 5 5 2 3 1 2 2 1 4 3 4 5
## [68941] 1 1 1 5 5 5 3 5 4 3 3 5 3 3 5 2 2 3 1 2 5 5 5 3 2 2 2 1 1 5 4 1 5 1 4 4
## [68977] 5 3 2 3 5 4 3 2 4 4 3 4 1 1 5 2 2 2 1 3 2 1 5 1 4 1 2 2 5 1 5 4 2 1 3 5
## [69013] 4 4 1 1 4 5 3 2 2 3 2 4 1 4 1 1 3 4 2 1 3 4 2 3 3 5 2 5 1 3 1 4 3 3 3 1
## [69049] 3 5 2 4 1 1 3 3 1 4 4 4 4 3 1 3 5 2 1 4 2 4 1 1 2 4 5 4 3 3 3 4 3 5 3 5
## [69085] 2 4 3 5 3 3 2 3 2 2 5 3 3 1 5 1 3 3 5 3 4 2 3 2 4 2 5 4 3 5 1 1 2 3 4 5
## [69121] 3 3 2 1 3 4 1 3 1 2 2 5 3 5 1 2 4 1 4 4 1 5 1 3 1 5 3 1 2 1 2 1 1 1 2 5
## [69157] 4 3 5 4 4 2 1 3 5 4 3 3 2 2 4 3 5 2 5 1 5 5 1 2 5 5 3 2 5 2 4 4 4 5 5 5
## [69193] 3 5 2 2 1 2 3 2 5 1 2 3 2 2 2 1 3 4 1 5 1 2 5 2 1 1 2 2 1 3 2 2 3 2 3 2
## [69229] 3 1 3 1 4 1 3 1 2 1 4 4 2 2 3 4 3 2 1 1 5 1 2 2 5 4 1 3 1 3 3 3 2 2 1 1
## [69265] 1 5 2 1 3 5 2 4 5 2 5 2 4 5 2 1 2 5 4 1 2 5 3 1 4 5 4 3 1 2 3 3 1 5 3 1
## [69301] 2 2 2 2 1 4 5 1 3 1 4 1 4 3 3 2 1 2 1 2 3 5 3 1 2 5 5 2 4 3 5 4 4 2 5 5
## [69337] 3 4 4 4 1 5 5 4 1 2 4 4 2 5 1 2 2 3 3 1 5 5 4 3 1 3 5 2 1 5 5 4 3 1 4 2
## [69373] 2 3 4 2 2 1 1 2 4 1 1 3 5 5 3 1 2 2 2 4 2 1 1 4 4 4 5 1 3 4 3 1 3 1 1 3
## [69409] 5 3 5 5 4 2 1 4 5 5 1 5 1 4 1 4 4 2 4 2 3 4 1 5 5 1 5 3 2 2 1 1 4 5 2 5
## [69445] 3 2 5 1 5 4 1 3 5 1 2 1 1 2 4 3 4 4 3 3 1 5 3 4 2 4 2 1 1 1 3 4 3 3 5 2
## [69481] 1 5 1 5 3 1 2 2 5 5 4 2 4 2 2 1 4 2 3 1 1 4 1 2 3 5 4 3 5 1 5 4 4 5 2 2
## [69517] 2 5 2 2 2 2 3 3 4 2 4 5 5 5 3 4 2 3 1 4 5 2 2 1 2 2 4 4 1 4 5 5 3 5 1 2
## [69553] 1 1 2 5 2 4 2 2 4 5 1 4 2 5 3 5 5 3 1 5 4 5 1 1 4 4 1 1 3 2 3 3 1 4 3 2
## [69589] 2 4 4 3 3 1 1 3 2 4 3 1 1 3 4 2 4 4 5 1 5 1 3 3 2 5 4 2 3 4 3 1 3 4 3 5
## [69625] 5 3 4 2 3 5 3 2 4 2 4 4 1 4 4 2 5 3 3 4 5 4 2 2 3 5 4 1 1 3 3 5 4 5 4 3
## [69661] 1 5 2 5 3 5 1 1 3 1 3 2 3 3 2 5 4 5 4 2 5 5 2 2 2 4 2 2 4 5 5 5 3 5 1 3
## [69697] 4 3 4 2 5 5 3 2 2 2 2 2 4 5 3 2 1 5 4 3 3 1 5 4 3 4 1 4 3 1 4 2 1 1 2 5
## [69733] 3 5 5 3 1 3 3 4 5 5 2 2 2 4 5 4 3 5 1 1 5 1 2 4 4 5 2 1 2 5 1 4 5 5 3 4
## [69769] 3 5 5 5 4 4 5 3 5 3 2 2 4 5 5 3 2 1 5 1 3 4 1 4 2 4 1 1 5 5 3 5 1 1 4 4
## [69805] 4 1 1 1 4 5 5 2 1 2 3 3 1 4 5 3 1 3 2 5 1 3 1 5 3 5 1 1 4 3 5 4 4 5 3 5
## [69841] 3 1 1 5 2 1 1 1 4 5 3 3 4 2 5 2 1 2 4 5 1 5 5 1 3 5 3 1 4 4 2 4 5 3 5 1
## [69877] 1 3 5 5 1 1 2 1 4 4 2 1 5 2 5 2 4 4 1 2 1 1 2 3 2 2 4 3 1 1 4 2 2 5 5 3
## [69913] 3 4 5 4 2 1 5 5 3 5 4 5 2 5 5 3 1 1 4 2 4 3 3 5 3 1 2 4 5 2 3 5 5 5 1 1
## [69949] 3 5 2 4 2 3 4 1 1 3 1 5 3 3 4 5 1 3 5 2 5 2 3 5 4 2 1 3 5 4 5 4 2 5 3 2
## [69985] 5 1 5 1 3 5 1 1 5 4 2 1 1 1 2 1 4 2 1 1 1 5 4 3 1 5 2 2 1 1 4 4 3 4 5 2
## [70021] 3 1 4 1 1 2 3 2 4 4 4 5 5 3 5 3 5 4 1 1 2 3 4 2 5 4 2 5 3 2 3 2 2 3 4 1
## [70057] 1 2 1 3 5 2 1 1 1 1 4 4 2 1 2 2 4 2 3 5 5 4 5 1 1 3 4 2 1 2 2 1 3 3 2 4
## [70093] 4 3 4 1 1 2 1 2 5 4 5 4 4 1 3 4 2 1 1 2 5 5 2 2 2 1 1 4 2 3 3 3 4 1 1 3
## [70129] 3 4 2 5 3 1 1 1 4 4 4 1 1 1 4 1 3 4 2 4 3 3 1 1 2 1 3 5 1 5 2 1 5 5 1 1
## [70165] 4 1 1 3 2 5 5 4 2 2 4 5 1 5 1 5 4 5 1 1 3 5 2 1 5 1 2 3 4 2 3 5 5 3 4 4
## [70201] 2 1 5 4 1 3 5 2 3 1 2 5 1 5 1 1 1 5 4 3 1 2 3 5 3 4 5 5 3 1 4 2 2 5 2 3
## [70237] 3 3 5 3 2 1 4 2 4 2 1 4 1 4 3 4 3 5 3 2 2 4 4 3 2 5 2 1 4 2 3 3 3 5 1 2
## [70273] 2 1 1 1 4 3 4 4 5 1 1 5 1 3 5 2 1 3 5 4 5 1 4 1 5 3 4 3 4 3 1 3 5 5 5 5
## [70309] 3 5 3 1 3 3 2 2 2 3 4 5 5 2 1 4 2 2 5 4 5 4 1 1 4 2 4 5 3 4 4 4 2 5 3 2
## [70345] 3 2 5 5 1 5 1 2 1 1 1 2 1 1 3 4 5 4 4 3 2 1 5 5 4 2 1 5 4 1 2 5 4 3 3 3
## [70381] 1 2 2 2 2 2 3 1 5 1 1 3 4 4 3 4 2 3 2 5 2 3 1 1 3 2 3 1 2 3 4 4 5 1 3 2
## [70417] 5 5 1 4 1 3 5 5 3 3 2 2 1 5 3 3 2 1 1 5 1 4 2 4 5 5 4 4 3 4 2 5 5 1 4 5
## [70453] 2 1 3 5 2 3 5 1 4 5 5 1 3 2 1 4 4 2 4 1 5 3 1 2 1 5 5 1 2 4 4 1 3 1 4 3
## [70489] 5 4 4 2 1 1 3 1 4 2 2 1 1 4 4 3 4 1 3 5 2 1 1 2 2 2 2 2 1 1 1 2 4 5 2 5
## [70525] 5 2 2 5 2 5 1 1 4 5 3 3 5 4 4 4 3 5 1 3 5 3 2 4 2 2 2 1 1 2 5 5 2 5 1 3
## [70561] 3 3 4 4 4 5 2 4 4 4 5 2 2 1 2 5 4 1 1 3 1 4 2 3 1 5 3 4 5 5 5 2 4 3 4 4
## [70597] 4 5 3 2 1 1 1 2 2 1 2 5 2 3 5 2 3 3 1 3 2 4 3 3 3 1 3 3 1 1 5 4 3 3 3 4
## [70633] 2 2 2 4 3 2 1 3 2 4 5 2 4 3 4 2 2 5 2 2 4 3 5 2 5 1 4 3 4 5 4 2 2 1 4 2
## [70669] 5 3 2 1 4 3 2 1 4 3 4 5 3 3 1 2 2 4 2 1 3 3 4 2 5 1 1 2 2 1 1 5 3 1 5 3
## [70705] 3 4 5 5 2 4 4 2 3 3 4 2 1 2 2 3 1 5 4 3 3 4 5 4 5 4 4 4 2 2 1 1 1 5 2 5
## [70741] 4 3 2 1 4 4 1 2 4 1 3 1 3 2 3 1 5 4 5 2 5 2 5 5 3 4 4 4 3 4 5 1 5 5 5 2
## [70777] 4 2 5 3 4 1 2 5 3 5 1 2 3 1 3 5 3 4 2 1 2 2 2 2 3 4 4 3 4 4 5 4 5 4 1 4
## [70813] 2 5 1 5 2 1 5 4 1 3 2 2 4 4 2 3 5 3 3 2 3 5 3 2 2 4 2 3 2 5 3 3 3 3 3 2
## [70849] 4 5 4 2 2 2 4 4 4 1 4 5 2 5 1 1 4 3 1 1 4 3 2 3 5 1 5 2 1 3 4 4 1 4 1 2
## [70885] 4 4 4 1 3 2 5 5 2 5 2 5 2 3 5 2 4 1 2 2 1 4 2 1 5 1 3 3 3 3 4 1 3 3 5 1
## [70921] 1 3 4 5 4 4 2 1 5 1 4 5 2 5 4 1 3 2 4 5 5 3 2 1 1 4 2 2 3 5 4 3 4 4 2 4
## [70957] 5 4 1 1 3 4 5 2 3 1 1 3 1 5 2 2 3 5 2 2 2 3 2 4 2 1 4 2 2 5 1 4 4 4 5 3
## [70993] 4 5 2 4 4 4 2 4 1 1 4 4 5 2 4 4 3 1 2 5 1 4 5 5 3 5 5 4 1 4 1 5 5 5 3 1
## [71029] 1 3 1 1 2 2 5 2 4 4 1 2 2 3 5 5 5 1 2 5 2 5 5 5 4 2 2 1 2 3 1 3 3 5 5 1
## [71065] 1 3 5 2 3 1 1 1 1 4 5 1 4 5 3 5 5 2 1 3 1 1 1 5 5 1 2 2 3 1 2 5 2 1 2 4
## [71101] 5 5 4 4 1 1 1 4 4 1 4 1 5 2 3 4 1 1 5 1 5 3 3 4 3 2 5 4 2 4 3 1 2 4 3 2
## [71137] 5 3 2 4 1 1 3 1 2 1 3 5 2 3 3 2 3 3 3 1 3 1 2 5 3 1 1 2 1 3 1 1 4 2 1 5
## [71173] 3 5 3 2 3 1 2 1 3 2 3 5 4 4 1 5 2 3 3 2 3 3 3 2 1 4 1 4 3 4 3 2 3 4 1 1
## [71209] 3 4 2 5 2 1 5 3 1 5 3 2 1 4 2 1 4 5 4 1 1 5 4 5 5 2 5 5 5 3 3 3 5 4 5 4
## [71245] 2 4 1 4 4 4 3 1 2 1 2 4 2 4 1 3 2 2 1 1 1 3 1 4 5 2 1 2 2 2 1 5 4 2 2 4
## [71281] 2 4 3 4 3 1 5 5 1 4 4 3 2 5 2 5 1 3 4 3 4 3 1 4 4 3 2 2 3 1 5 3 5 3 1 4
## [71317] 4 4 1 5 2 3 1 1 5 4 5 3 1 1 4 5 1 1 1 4 2 1 3 3 2 5 2 5 3 1 3 3 1 5 3 2
## [71353] 2 3 5 2 1 3 2 3 4 3 4 4 4 1 3 1 4 2 3 5 2 4 4 4 4 5 1 4 3 2 5 5 4 5 2 1
## [71389] 4 3 5 2 1 1 4 1 1 1 5 1 3 1 5 5 5 3 1 4 2 2 4 4 5 2 3 3 3 2 2 4 3 3 1 1
## [71425] 4 5 3 4 3 2 2 3 3 4 2 2 3 1 1 4 1 2 3 4 5 3 1 4 3 4 2 4 4 5 5 4 4 3 3 3
## [71461] 4 5 2 5 5 5 5 3 1 3 5 3 3 4 1 1 3 1 5 3 3 2 2 2 2 2 2 5 1 3 2 4 5 2 5 5
## [71497] 1 2 4 1 1 3 3 5 5 1 1 4 2 1 3 3 5 5 5 3 4 2 3 4 3 2 2 3 3 4 4 3 3 3 3 1
## [71533] 3 4 3 1 5 5 5 1 4 2 1 1 4 3 3 2 1 2 3 3 1 1 1 3 3 3 1 4 2 3 4 1 2 5 5 1
## [71569] 5 5 3 4 3 2 5 2 2 1 2 3 3 2 1 1 4 5 5 4 1 5 3 5 4 4 3 2 5 3 4 2 2 5 2 4
## [71605] 2 1 5 5 4 4 2 1 2 2 3 5 2 5 2 1 1 2 4 2 2 2 3 4 5 3 2 2 2 3 4 1 5 5 4 2
## [71641] 3 3 2 5 1 2 5 2 3 4 4 3 3 1 2 3 1 4 3 2 2 2 1 2 4 5 2 3 2 1 2 1 3 3 1 5
## [71677] 3 2 2 3 4 4 2 5 2 1 5 3 2 1 5 1 3 5 2 5 1 4 4 3 2 2 2 1 4 4 4 1 4 2 3 3
## [71713] 3 3 1 2 3 5 5 1 4 3 4 2 3 4 1 4 1 4 4 5 5 3 5 4 1 3 4 4 5 1 3 2 3 1 5 4
## [71749] 4 3 2 2 3 5 2 3 4 2 5 5 3 3 5 3 1 1 1 4 4 2 1 2 1 4 2 2 5 2 3 5 5 2 2 3
## [71785] 4 5 4 4 4 5 2 2 3 4 3 3 4 5 4 2 4 3 5 2 4 2 3 2 2 4 2 5 1 2 3 3 4 5 5 5
## [71821] 5 1 3 1 4 5 1 4 3 4 4 1 5 1 5 3 1 3 2 1 4 5 5 5 2 4 3 1 4 4 4 4 1 2 1 1
## [71857] 3 3 5 1 2 1 1 4 5 2 1 4 4 2 3 4 5 1 5 1 2 5 5 5 3 3 5 2 2 3 1 5 1 3 2 4
## [71893] 1 5 3 5 4 1 1 2 5 1 2 4 3 3 2 5 4 3 4 5 2 1 2 3 2 2 2 5 3 5 5 5 4 4 3 1
## [71929] 1 5 3 3 5 5 5 1 4 3 4 1 3 5 3 2 4 4 5 5 5 2 4 1 3 5 3 3 4 5 3 1 3 2 4 4
## [71965] 4 4 1 4 4 2 1 5 3 3 4 1 5 4 3 2 2 5 4 2 5 3 1 2 3 3 1 5 5 2 4 5 3 1 4 5
## [72001] 5 3 3 2 5 1 1 3 5 3 1 1 1 4 2 2 1 1 4 5 2 3 5 1 3 5 2 5 3 5 4 5 3 5 1 1
## [72037] 5 3 5 3 1 1 3 1 5 2 3 2 2 2 5 2 1 5 5 1 4 1 2 1 5 4 3 1 1 3 1 4 2 5 1 4
## [72073] 3 3 5 3 2 1 1 3 4 1 4 2 4 5 4 4 4 1 1 1 1 1 3 5 1 1 2 1 2 3 1 5 4 4 2 2
## [72109] 3 2 4 3 2 1 1 1 5 3 1 4 4 4 4 1 1 2 4 5 2 3 4 3 2 3 3 3 3 4 5 2 3 5 1 2
## [72145] 2 3 1 3 2 1 2 5 1 1 4 5 1 3 5 5 2 5 1 1 4 1 3 3 5 3 3 5 4 3 1 3 3 5 1 2
## [72181] 3 1 3 4 5 3 4 2 1 4 1 5 3 3 2 2 5 1 2 1 1 1 4 1 3 3 3 1 3 4 4 2 5 1 2 5
## [72217] 1 2 3 5 1 3 4 2 4 4 5 1 5 1 2 5 1 4 5 2 3 2 1 5 2 5 3 5 5 1 4 1 2 1 5 2
## [72253] 4 1 2 2 3 2 2 3 1 4 3 3 5 4 5 5 1 2 2 4 1 2 3 5 2 3 5 2 2 1 2 1 3 3 1 1
## [72289] 4 3 4 3 4 5 1 3 4 3 4 1 2 5 2 5 1 2 1 3 1 2 4 3 1 2 3 5 2 4 2 5 3 4 3 2
## [72325] 1 2 5 3 2 5 4 2 1 1 2 5 3 1 4 5 5 4 3 3 5 3 4 1 3 5 5 5 1 2 4 5 1 1 5 2
## [72361] 2 3 1 2 2 5 4 3 5 4 4 3 3 3 3 4 5 3 4 2 3 5 4 4 3 2 4 1 4 4 2 1 3 1 3 1
## [72397] 4 5 5 4 2 4 3 2 3 4 5 5 1 4 3 3 3 3 4 3 3 4 5 3 2 1 5 3 2 3 1 5 3 1 3 2
## [72433] 3 1 5 4 4 3 5 3 4 1 4 2 2 4 1 1 2 3 3 3 4 3 2 3 3 2 2 1 3 4 2 5 5 1 5 3
## [72469] 1 2 1 2 5 1 4 4 4 4 4 4 3 4 5 5 1 1 4 3 3 3 2 4 2 4 5 3 5 1 1 4 5 3 5 2
## [72505] 4 4 4 5 4 5 2 1 5 4 5 2 4 5 1 5 3 3 1 4 2 4 2 1 3 5 3 2 2 3 2 1 3 3 4 1
## [72541] 3 5 5 3 3 4 5 1 5 4 3 2 2 1 4 2 5 4 5 3 3 2 3 4 4 4 4 5 2 2 1 1 3 2 4 1
## [72577] 1 5 3 3 5 4 2 2 4 2 4 3 5 5 4 1 5 2 4 4 1 1 1 4 3 3 4 4 4 1 4 1 2 2 5 4
## [72613] 4 4 1 4 2 1 4 5 2 2 3 3 5 4 4 3 3 1 1 2 5 3 5 3 5 4 2 3 5 1 5 1 2 3 5 2
## [72649] 4 4 2 1 3 2 4 5 1 5 1 1 5 1 3 2 4 3 2 2 4 2 3 4 3 2 1 3 2 1 3 5 4 4 4 1
## [72685] 5 5 5 5 2 3 1 5 5 3 4 1 5 2 2 1 4 2 2 4 1 5 1 2 4 4 4 1 2 2 4 5 4 5 2 4
## [72721] 2 5 2 3 5 1 4 4 2 5 4 3 5 3 4 5 3 4 5 1 5 1 2 1 3 1 1 5 3 3 3 2 4 2 4 5
## [72757] 4 3 5 4 4 4 3 1 4 4 1 1 5 3 3 5 2 2 2 1 2 4 2 3 5 5 3 1 5 3 2 3 3 4 3 2
## [72793] 4 2 5 2 3 3 5 3 3 3 2 3 1 3 5 2 4 1 1 2 3 2 5 5 5 5 3 4 3 4 5 1 1 1 5 3
## [72829] 5 2 2 2 4 1 2 3 1 3 4 5 1 2 1 3 1 3 3 4 4 2 3 4 4 1 3 5 5 2 4 3 2 2 3 4
## [72865] 5 4 1 4 2 3 3 5 1 5 1 5 4 5 4 3 1 2 1 5 5 1 5 5 1 4 2 5 4 3 3 3 4 4 1 3
## [72901] 4 3 5 4 4 5 4 4 5 2 5 3 4 5 2 1 1 3 5 1 3 4 2 3 2 4 1 1 5 2 4 4 3 3 4 3
## [72937] 1 1 4 3 3 1 1 4 3 2 4 1 4 1 3 5 1 1 1 3 3 3 4 3 4 5 1 2 5 3 4 3 3 4 1 2
## [72973] 1 3 4 2 3 2 2 3 1 4 3 2 5 2 3 4 2 5 2 2 3 5 1 5 5 3 2 3 4 2 5 1 1 3 3 1
## [73009] 4 2 4 1 3 2 2 5 4 3 4 3 1 4 1 5 4 5 2 2 5 2 4 1 3 4 2 1 3 3 1 1 5 1 1 5
## [73045] 4 5 4 2 1 3 1 3 1 4 5 1 4 1 3 4 4 3 4 5 1 5 4 1 5 5 3 1 3 1 3 5 4 3 2 3
## [73081] 3 3 1 3 2 5 5 3 3 3 4 2 3 1 4 3 5 5 5 1 5 3 3 2 4 3 4 1 4 5 4 2 2 5 1 1
## [73117] 5 5 1 5 5 4 2 2 2 3 2 1 4 1 4 2 3 3 2 2 5 4 4 2 2 2 2 2 3 5 2 5 5 3 5 4
## [73153] 5 3 2 3 3 5 5 4 3 2 1 1 2 2 1 1 3 1 3 2 4 5 4 2 4 5 3 3 3 2 4 1 1 5 2 3
## [73189] 4 3 4 5 4 3 1 4 5 5 4 4 5 2 5 1 3 1 4 3 4 3 1 4 5 4 3 5 3 5 1 1 2 5 1 4
## [73225] 2 5 4 4 5 4 3 2 3 3 3 2 4 1 5 4 5 1 5 1 1 2 4 5 4 4 5 1 3 5 1 5 2 4 1 2
## [73261] 2 1 1 2 2 5 2 5 2 5 3 2 1 1 3 2 4 2 3 1 3 5 1 2 5 2 3 1 3 4 2 3 1 4 2 3
## [73297] 4 5 1 2 5 1 2 1 3 4 2 5 1 4 3 4 1 5 3 4 2 2 3 5 2 5 5 4 5 2 4 1 1 2 4 3
## [73333] 4 4 2 5 4 3 5 4 5 1 5 4 5 3 1 5 4 4 2 3 1 1 2 5 2 1 5 5 5 2 1 1 4 4 1 1
## [73369] 3 5 4 3 1 2 2 3 4 4 5 4 2 2 5 4 4 5 4 3 4 4 3 3 1 2 5 4 5 1 5 2 1 5 3 2
## [73405] 5 1 3 3 5 2 2 1 2 4 5 4 4 3 5 4 1 4 3 1 4 4 5 3 2 2 4 1 4 3 2 1 5 2 4 1
## [73441] 3 5 1 4 1 3 5 1 4 5 3 3 2 1 3 4 5 5 3 5 1 4 5 1 1 2 2 5 2 4 3 4 5 3 2 2
## [73477] 2 1 1 1 4 5 1 5 3 3 5 3 2 1 3 5 3 1 4 2 3 1 2 1 1 5 1 4 1 2 5 5 1 3 3 4
## [73513] 4 4 5 4 5 1 2 3 1 2 3 5 2 5 3 5 1 2 5 4 2 1 2 1 2 2 3 5 4 1 2 1 4 3 1 5
## [73549] 4 5 1 5 4 2 1 4 4 2 3 2 2 2 4 1 5 1 2 2 4 3 2 2 3 1 1 1 2 3 4 2 2 4 4 5
## [73585] 4 1 5 4 2 1 2 1 2 4 1 5 1 3 5 1 5 3 2 5 5 1 1 5 1 1 2 4 4 2 1 3 4 5 4 1
## [73621] 5 5 2 5 3 2 1 2 3 2 2 5 3 1 5 4 4 5 5 4 3 2 4 5 4 2 1 5 5 2 4 3 3 1 4 3
## [73657] 4 4 5 3 3 3 4 4 2 1 1 5 1 4 2 4 1 4 3 5 3 2 3 4 2 2 3 3 3 3 4 5 1 3 4 4
## [73693] 4 3 1 2 1 1 2 3 1 2 3 5 3 1 3 5 5 5 3 5 3 4 1 3 5 3 2 4 2 2 1 3 3 4 5 4
## [73729] 5 1 2 5 3 4 2 1 3 2 5 5 2 2 5 5 4 5 2 2 1 2 4 5 5 4 2 3 2 4 1 3 3 4 1 3
## [73765] 2 2 1 4 5 3 4 4 5 2 2 5 5 2 3 2 5 1 5 3 2 3 4 4 3 1 1 2 2 3 3 4 5 2 2 4
## [73801] 5 4 3 4 5 1 4 3 5 5 4 5 5 2 2 3 3 1 5 3 1 3 5 1 1 4 5 1 2 3 5 3 4 1 4 3
## [73837] 2 2 2 5 4 1 3 4 1 4 2 4 3 2 2 4 5 1 1 1 1 5 1 3 4 3 4 4 2 3 2 5 5 1 4 3
## [73873] 2 1 4 4 5 3 5 1 5 2 3 5 3 1 3 2 1 5 5 3 3 2 5 3 4 5 5 3 4 1 2 5 5 2 3 2
## [73909] 5 5 4 2 5 1 5 2 2 1 4 2 3 5 3 1 2 2 2 4 1 3 3 2 4 4 1 3 4 5 3 1 1 1 5 1
## [73945] 2 1 4 3 5 2 1 4 4 3 4 5 4 5 4 2 3 5 1 2 1 2 2 1 3 2 1 4 2 3 5 2 5 4 2 2
## [73981] 1 3 5 2 1 5 5 1 1 4 5 3 3 4 4 3 1 2 5 3 4 3 5 2 4 3 2 2 3 5 1 3 3 2 3 5
## [74017] 4 5 3 1 3 3 3 5 3 3 5 4 3 3 2 3 4 3 4 4 2 1 1 3 5 5 2 2 5 2 3 4 2 3 5 4
## [74053] 1 2 2 3 4 5 1 5 1 3 4 2 5 2 3 1 4 5 2 5 1 3 5 5 2 5 1 1 3 1 2 3 2 3 3 2
## [74089] 5 1 4 3 4 2 2 2 1 5 2 3 2 4 3 4 4 1 1 1 5 5 3 2 1 2 2 3 3 4 2 1 5 2 1 3
## [74125] 4 5 4 4 3 5 4 5 4 4 5 3 4 1 4 3 2 4 4 5 5 1 3 5 2 4 5 2 5 4 2 2 1 1 4 2
## [74161] 1 4 3 5 3 3 5 3 2 5 1 4 4 3 1 5 4 2 4 2 2 3 2 2 2 1 5 1 2 2 3 4 1 4 2 4
## [74197] 3 3 1 3 1 3 2 3 2 4 2 4 1 5 1 4 1 4 4 2 5 5 4 5 3 3 5 3 5 2 3 5 5 2 3 2
## [74233] 5 5 1 2 5 4 2 2 5 1 3 2 1 1 2 1 1 4 3 2 2 3 4 1 2 4 3 5 5 1 3 4 1 5 3 4
## [74269] 3 2 4 2 1 3 3 1 3 2 2 5 1 1 5 5 3 2 5 1 5 4 5 3 3 2 3 4 1 2 1 5 5 3 5 2
## [74305] 1 5 1 3 5 3 1 4 2 2 1 3 3 3 3 5 4 4 1 5 1 3 3 5 2 2 1 2 2 1 5 1 3 2 2 5
## [74341] 1 1 4 3 3 5 2 1 3 2 3 1 1 4 4 1 2 4 1 3 4 1 3 1 4 2 4 5 3 5 4 3 3 4 1 4
## [74377] 1 3 3 3 4 2 5 4 5 4 5 2 5 5 2 1 1 4 1 1 3 4 1 2 5 3 4 4 1 3 4 3 5 1 2 5
## [74413] 2 5 1 1 3 3 2 4 5 2 3 2 3 5 4 5 5 5 4 5 2 2 3 3 1 2 3 1 5 1 1 5 1 4 5 3
## [74449] 1 1 2 1 4 2 4 3 3 1 1 4 5 5 5 5 1 1 2 1 1 1 5 2 5 5 1 1 5 5 3 4 5 5 3 4
## [74485] 4 5 1 3 3 4 3 3 2 5 1 2 5 2 4 2 2 2 2 3 3 5 2 5 5 2 3 3 1 4 3 5 4 2 3 1
## [74521] 3 4 3 4 4 3 2 3 1 2 4 5 4 3 5 2 4 4 4 2 4 2 4 1 4 5 2 1 5 3 5 2 3 5 2 4
## [74557] 3 2 2 4 5 3 2 2 5 1 4 5 1 5 5 2 1 4 5 5 2 1 1 5 2 1 2 5 5 4 4 3 2 4 2 2
## [74593] 3 1 1 5 2 5 1 2 3 3 2 1 1 1 5 2 3 3 2 4 5 2 2 3 3 3 5 4 5 1 3 2 5 2 3 3
## [74629] 3 5 3 1 3 5 1 1 5 3 1 5 4 3 3 4 4 5 5 3 1 3 2 3 4 1 3 5 5 1 4 2 4 4 3 4
## [74665] 1 2 2 4 4 2 4 1 1 3 5 5 1 4 3 3 1 1 2 2 2 4 2 3 1 5 4 2 4 5 1 3 3 5 4 3
## [74701] 1 3 5 1 4 2 5 1 2 2 1 5 3 3 4 5 4 4 1 3 4 2 3 5 3 3 2 3 3 2 4 5 1 5 5 3
## [74737] 5 2 4 1 1 2 2 4 2 1 4 3 1 2 1 4 1 4 5 3 5 4 4 1 2 2 2 5 5 4 4 3 3 1 4 1
## [74773] 2 5 4 1 2 4 5 4 5 5 1 1 3 1 4 2 3 2 1 5 5 1 1 4 3 5 4 2 2 5 5 3 4 2 4 3
## [74809] 4 5 5 1 3 4 2 1 1 2 4 3 2 4 1 5 3 4 3 1 4 5 2 2 5 1 1 1 3 5 5 5 4 1 5 5
## [74845] 1 2 1 4 4 5 1 2 1 5 3 1 3 1 4 5 4 1 2 4 3 1 2 2 5 2 2 1 3 5 5 5 4 2 1 3
## [74881] 5 2 5 4 5 2 1 5 1 2 5 4 1 4 4 3 3 5 4 3 3 1 4 1 3 5 1 5 3 4 1 3 3 1 2 5
## [74917] 1 4 4 2 3 5 4 1 1 2 3 4 1 3 4 5 4 3 1 4 3 4 1 5 3 4 2 5 2 2 5 1 3 2 3 4
## [74953] 2 4 5 5 1 4 1 5 5 3 4 4 5 1 5 5 5 2 5 3 3 2 2 3 4 4 1 1 2 4 5 2 3 1 2 4
## [74989] 5 3 2 1 1 2 1 5 1 4 1 1 5 2 2 2 2 3 2 2 3 2 2 5 4 5 5 3 5 1 2 1 1 3 5 4
## [75025] 5 5 2 3 4 5 5 1 1 1 1 2 1 4 4 5 5 1 1 5 5 1 4 1 3 1 1 5 3 5 4 5 2 3 5 4
## [75061] 3 1 5 2 4 4 5 5 1 1 2 5 5 1 5 3 2 4 4 5 4 5 1 3 1 4 3 1 1 5 3 5 4 5 5 5
## [75097] 4 1 2 3 3 1 1 4 5 4 4 2 5 2 5 3 5 2 4 4 3 4 2 4 3 3 4 1 5 4 4 4 5 3 1 2
## [75133] 4 3 5 3 1 4 3 4 1 3 1 2 5 2 3 4 1 2 3 1 4 2 2 3 1 3 3 2 2 4 3 5 4 1 4 1
## [75169] 1 4 1 4 3 3 1 1 3 3 1 4 4 4 3 1 3 1 5 3 2 5 1 5 2 4 1 5 5 3 2 1 3 2 1 5
## [75205] 2 3 4 5 1 3 2 4 4 2 4 4 5 2 5 5 5 4 4 2 1 5 5 3 4 5 4 2 1 4 3 1 4 3 3 2
## [75241] 1 4 2 3 1 2 4 3 2 3 3 1 3 2 4 3 2 1 1 3 2 4 3 4 5 2 3 5 5 2 5 5 2 1 2 2
## [75277] 5 2 1 4 2 2 2 3 2 3 1 5 4 5 4 4 3 1 2 4 2 2 5 2 5 3 1 4 4 3 1 5 4 3 4 3
## [75313] 3 1 3 1 1 5 1 1 4 3 1 1 1 1 5 5 1 1 1 5 1 3 4 3 4 5 1 3 3 5 2 4 5 2 3 2
## [75349] 2 1 5 3 2 4 3 1 4 4 1 3 1 3 3 3 5 3 2 3 5 2 4 5 5 1 3 3 3 4 3 5 5 2 3 3
## [75385] 4 4 4 5 4 4 2 4 1 2 5 1 2 5 2 5 1 3 3 5 4 2 4 2 1 2 3 2 2 3 1 1 5 5 4 2
## [75421] 4 3 1 2 1 4 5 5 1 5 1 1 3 4 2 5 2 4 5 1 4 5 1 3 4 2 5 3 4 4 3 2 1 4 1 4
## [75457] 5 1 2 4 4 4 4 5 5 4 4 4 5 5 3 3 2 1 2 5 2 1 2 1 1 2 2 3 2 4 4 5 4 5 3 1
## [75493] 5 3 2 4 1 2 1 3 5 2 4 2 5 3 3 4 2 5 2 1 4 1 3 5 5 3 1 4 3 2 1 2 1 2 1 4
## [75529] 5 3 5 1 4 4 1 4 3 3 3 5 3 5 2 1 1 1 1 2 3 3 4 3 1 2 5 5 5 3 3 3 1 2 2 5
## [75565] 5 1 4 2 5 4 1 5 3 2 3 5 4 1 1 5 3 4 4 4 5 3 1 1 5 2 1 4 3 3 5 4 5 5 4 4
## [75601] 3 3 2 3 1 2 4 4 4 2 4 4 4 3 5 4 1 5 1 5 5 5 5 2 3 2 4 2 4 5 1 5 3 3 2 1
## [75637] 4 2 2 4 5 4 1 2 1 1 4 3 4 2 4 3 2 3 3 5 5 5 3 3 3 1 4 1 1 3 4 5 2 2 5 1
## [75673] 2 5 4 4 1 4 1 1 3 3 4 1 1 5 5 2 5 5 5 2 3 4 2 2 5 4 1 4 3 1 5 4 4 5 1 5
## [75709] 4 4 2 3 2 4 3 5 5 4 1 3 3 5 1 5 1 1 2 3 2 2 2 3 3 3 3 2 4 3 1 1 5 5 4 1
## [75745] 2 3 5 1 1 1 3 2 1 4 2 3 2 2 1 5 2 1 5 3 1 1 1 2 2 1 1 5 2 2 4 5 3 4 5 4
## [75781] 3 2 4 1 5 1 1 5 4 2 2 4 5 2 4 3 4 5 2 3 3 3 1 2 3 2 1 1 5 3 2 2 3 3 5 5
## [75817] 1 3 3 5 4 4 3 4 5 1 1 3 1 4 2 3 4 4 1 1 2 4 4 5 5 3 2 4 3 3 2 5 2 1 3 3
## [75853] 1 4 5 1 1 4 5 1 3 3 2 5 2 1 3 4 5 1 2 3 4 1 4 5 2 2 2 3 2 3 5 1 5 1 2 1
## [75889] 3 4 5 1 2 3 4 3 3 3 1 2 3 2 4 1 4 3 5 5 2 3 1 2 4 2 4 1 1 2 1 4 5 3 2 4
## [75925] 2 4 2 4 3 1 4 5 2 1 4 1 2 4 3 4 3 1 1 5 1 4 5 3 4 1 3 1 4 4 5 3 4 4 5 3
## [75961] 1 2 3 3 3 1 1 5 1 2 1 5 4 1 3 3 2 5 4 4 5 2 2 2 4 3 1 2 3 2 4 4 4 5 1 4
## [75997] 5 2 2 1 2 5 4 3 4 3 2 3 2 4 3 3 3 3 1 1 4 2 1 5 5 3 3 3 5 3 1 4 5 2 5 5
## [76033] 5 3 2 3 4 2 5 5 5 2 4 3 4 3 1 4 5 5 3 1 4 4 4 2 3 5 5 1 2 2 2 2 1 3 1 5
## [76069] 3 1 4 3 2 4 5 2 1 4 5 2 2 1 4 3 4 5 3 1 4 4 4 5 3 4 5 4 5 1 2 2 2 4 2 5
## [76105] 3 4 3 5 2 3 3 5 3 3 3 1 1 3 2 1 1 3 3 2 5 2 4 1 3 2 1 4 5 1 3 3 4 1 5 1
## [76141] 4 5 1 5 2 4 2 4 3 4 2 2 3 1 5 1 1 4 5 4 3 4 5 2 1 1 2 4 5 4 2 3 5 4 2 3
## [76177] 2 2 2 1 1 3 3 4 4 4 5 4 3 4 3 5 1 5 5 1 1 4 2 3 2 3 1 2 1 5 4 4 2 2 1 2
## [76213] 1 2 5 5 3 4 3 4 4 4 3 1 2 4 4 4 4 2 5 3 5 1 2 4 1 1 1 1 2 5 3 1 5 3 1 4
## [76249] 5 4 1 5 1 4 2 4 2 2 5 5 5 3 1 5 5 5 3 5 1 2 2 1 1 3 2 2 4 4 2 2 1 1 5 5
## [76285] 5 2 4 4 2 2 5 2 2 4 1 4 5 2 4 4 1 5 1 1 3 1 1 3 3 1 4 1 2 2 5 2 4 2 4 3
## [76321] 4 3 5 3 5 3 5 5 2 1 4 4 3 4 4 1 4 3 3 5 4 5 2 2 4 5 4 2 5 3 5 3 4 5 3 4
## [76357] 3 3 4 3 2 2 4 3 1 2 1 3 2 1 1 4 5 1 2 2 4 1 3 2 1 2 5 4 2 1 5 2 3 5 4 4
## [76393] 5 4 3 2 1 4 3 4 1 3 4 1 2 1 2 2 3 2 2 5 5 3 1 3 3 5 3 1 4 2 3 4 4 1 5 4
## [76429] 5 2 2 2 2 4 2 1 2 3 5 1 3 4 3 2 3 5 2 4 1 2 2 3 3 4 4 3 3 2 1 5 1 4 2 3
## [76465] 4 3 3 4 2 4 3 4 4 2 2 2 3 4 1 3 5 3 2 3 2 3 4 3 5 1 4 3 1 2 3 2 3 4 3 1
## [76501] 2 1 3 1 1 2 3 1 4 4 3 4 3 2 4 5 4 3 3 3 5 3 3 2 4 4 5 2 2 4 2 3 5 3 5 2
## [76537] 2 2 1 3 1 2 3 1 4 5 3 4 1 1 2 4 2 5 1 4 2 4 3 4 1 5 3 2 4 1 5 2 3 4 4 5
## [76573] 4 1 2 5 4 4 2 5 1 4 5 3 1 4 4 5 5 2 2 2 5 3 3 5 3 1 5 1 5 3 5 3 1 1 3 4
## [76609] 3 2 3 3 4 5 5 3 3 5 2 3 5 4 4 4 3 4 4 3 4 1 3 3 3 5 4 3 5 2 4 2 1 3 3 1
## [76645] 2 3 4 1 2 2 2 2 2 2 4 2 1 2 3 2 5 2 4 1 4 1 4 5 1 2 1 2 3 2 2 1 2 1 2 3
## [76681] 3 5 4 2 1 5 4 4 2 2 2 4 2 1 2 3 2 5 1 5 5 3 2 3 4 1 5 1 4 4 2 5 1 3 5 4
## [76717] 4 4 2 2 3 4 5 4 3 3 5 1 4 2 4 3 3 1 4 3 4 1 3 3 1 5 1 1 5 5 2 1 5 2 3 1
## [76753] 3 4 4 1 1 2 2 4 1 4 1 4 2 2 1 4 1 1 3 4 2 3 4 3 1 4 3 3 3 3 4 2 1 2 1 1
## [76789] 5 4 3 3 1 3 1 5 1 2 1 2 1 4 5 3 4 4 1 5 4 2 1 2 5 1 3 3 3 4 3 4 1 5 1 3
## [76825] 2 2 2 4 5 2 3 5 5 5 1 5 2 5 2 1 5 5 2 3 3 5 2 3 4 4 1 2 4 4 2 2 5 3 1 3
## [76861] 3 5 2 4 4 1 1 2 2 2 2 3 5 1 4 1 2 2 2 2 2 4 2 2 2 5 5 4 2 3 1 5 2 2 3 2
## [76897] 5 4 3 1 5 3 2 3 1 3 4 1 4 4 4 4 5 3 5 4 4 3 3 3 3 2 2 5 4 5 5 4 1 2 3 3
## [76933] 1 5 4 1 4 3 1 1 3 4 5 3 3 2 1 4 1 5 5 1 5 3 1 3 4 1 3 2 3 5 5 3 5 3 4 5
## [76969] 2 3 1 4 2 3 4 3 2 4 1 2 5 2 4 5 5 3 5 2 3 4 4 3 5 4 3 1 2 3 5 2 3 4 1 1
## [77005] 3 1 1 4 3 5 4 3 5 4 1 4 3 4 1 4 2 2 3 1 1 5 5 4 5 5 3 5 5 2 2 4 3 5 2 2
## [77041] 2 2 5 5 4 3 3 4 5 5 1 2 4 3 4 4 4 4 1 3 1 4 4 4 4 4 2 1 1 3 1 5 1 5 2 4
## [77077] 3 3 3 2 2 3 3 5 4 5 2 3 3 5 4 3 4 4 1 3 5 1 2 5 4 2 4 2 3 4 5 1 1 2 3 4
## [77113] 3 3 5 1 2 1 3 3 2 5 2 1 4 2 1 3 5 5 3 2 4 2 4 1 1 5 2 4 5 2 5 2 4 4 4 2
## [77149] 3 5 2 2 1 3 1 1 2 4 1 4 2 1 3 4 2 2 5 1 4 1 1 4 3 1 1 5 1 2 4 2 4 1 4 1
## [77185] 3 1 4 3 1 3 4 1 3 3 2 1 5 3 4 4 2 5 1 3 5 1 1 1 3 2 5 5 3 4 4 3 1 1 4 3
## [77221] 1 2 3 5 1 3 1 3 4 1 2 5 2 4 4 5 2 1 4 3 3 4 1 5 2 4 2 5 2 5 1 2 3 2 4 5
## [77257] 2 1 3 4 4 1 4 3 4 1 5 3 1 3 2 3 5 4 1 1 2 5 5 3 2 2 2 5 5 4 1 3 2 2 3 2
## [77293] 2 4 5 5 2 5 5 5 2 3 1 1 1 3 1 2 4 3 5 1 1 1 1 3 5 5 3 3 2 1 5 1 2 1 2 5
## [77329] 2 5 5 2 2 5 5 4 1 3 3 1 2 2 1 3 1 3 2 3 2 1 1 4 4 2 4 4 5 2 3 5 5 5 5 5
## [77365] 2 3 2 5 5 4 2 2 1 3 1 5 1 5 1 4 5 5 5 3 3 5 2 2 2 3 5 2 4 5 5 1 2 3 1 3
## [77401] 5 4 4 2 5 5 3 5 1 5 3 3 2 3 5 2 4 5 4 2 4 3 5 3 2 1 3 3 1 3 3 5 3 4 2 1
## [77437] 1 4 2 3 1 5 3 4 2 2 3 2 2 5 3 1 1 2 1 5 5 4 5 3 5 3 1 1 1 3 5 4 5 1 1 3
## [77473] 5 3 4 2 5 4 1 4 4 1 4 3 3 1 1 2 2 5 2 5 2 1 3 5 4 5 3 3 5 5 2 2 1 4 4 2
## [77509] 5 4 3 5 1 5 2 4 4 4 2 1 5 2 4 2 4 3 1 4 3 2 1 3 2 2 5 1 3 2 5 1 4 1 4 3
## [77545] 1 5 3 5 5 2 4 4 4 2 4 4 2 3 3 5 3 3 2 5 4 3 1 5 3 1 5 3 3 5 5 5 2 2 5 3
## [77581] 3 2 3 4 5 2 3 2 2 1 1 4 1 3 1 4 4 3 5 4 2 3 4 5 2 4 5 5 5 2 2 5 2 1 5 1
## [77617] 1 2 5 1 5 3 1 2 4 5 3 5 1 4 1 5 4 5 4 5 4 1 1 1 5 2 2 2 4 4 4 3 3 5 1 2
## [77653] 5 3 3 4 5 4 4 4 3 2 5 5 5 5 4 5 4 3 3 3 3 5 5 2 4 5 1 4 5 5 2 3 2 2 4 2
## [77689] 5 1 2 5 4 3 5 3 1 4 1 2 1 5 1 4 1 1 2 2 2 1 2 1 4 4 3 5 5 5 3 4 3 5 4 2
## [77725] 4 4 2 1 3 3 1 3 2 4 4 2 3 5 3 5 4 1 4 3 2 1 1 4 5 5 1 4 5 4 2 1 5 5 5 2
## [77761] 5 4 4 4 1 3 3 1 2 3 2 2 2 4 2 4 3 5 3 4 2 2 5 3 2 1 5 2 1 2 2 2 5 2 5 1
## [77797] 4 5 1 5 2 3 1 4 1 5 3 2 3 2 4 3 1 3 3 3 5 3 1 2 3 1 3 4 2 4 4 2 2 2 4 2
## [77833] 2 5 3 3 1 1 5 1 2 3 1 2 4 1 5 3 4 1 1 5 1 3 1 2 5 4 3 4 5 3 4 4 5 4 5 1
## [77869] 1 4 4 1 5 2 3 1 3 4 5 4 5 5 1 1 3 3 3 3 1 5 3 4 1 3 2 4 2 2 4 1 5 3 5 3
## [77905] 4 5 3 4 4 4 1 1 5 2 4 2 4 1 1 3 4 5 4 5 3 5 4 2 1 5 1 4 3 1 2 2 1 3 4 3
## [77941] 2 5 5 2 3 5 2 1 3 5 5 3 5 5 4 5 4 3 3 2 4 2 2 4 3 5 5 3 1 5 1 3 4 1 3 2
## [77977] 4 3 5 5 4 1 4 3 5 1 4 3 3 4 1 3 3 4 5 4 4 1 5 3 1 5 5 5 1 4 5 1 4 3 3 3
## [78013] 2 3 4 4 3 2 3 3 1 5 3 1 5 3 3 3 4 4 3 4 5 1 4 3 2 4 3 2 1 5 2 3 3 1 1 5
## [78049] 3 2 4 1 3 3 2 3 4 4 5 4 4 4 5 2 4 5 2 3 5 5 1 5 4 5 2 4 5 1 5 4 5 1 1 4
## [78085] 5 3 2 2 3 5 5 5 3 3 2 2 5 4 5 4 2 5 4 5 2 2 2 5 1 2 3 2 3 2 5 5 2 5 5 4
## [78121] 2 3 2 5 3 4 5 2 3 2 5 2 1 2 3 3 2 4 5 5 1 2 5 2 1 4 4 2 5 2 3 3 2 5 2 4
## [78157] 1 2 1 4 4 1 3 4 3 3 2 5 3 4 5 3 2 2 3 4 2 2 3 2 3 4 1 5 3 2 1 1 5 2 3 1
## [78193] 3 5 2 2 2 5 3 1 3 4 3 1 3 1 4 3 2 5 2 5 1 4 2 2 5 1 1 1 3 5 4 2 1 3 5 2
## [78229] 5 4 1 5 2 1 3 2 5 2 2 1 5 1 4 2 1 3 3 1 1 2 3 1 3 5 5 5 4 1 4 5 4 4 3 2
## [78265] 4 5 2 4 1 4 1 2 3 3 4 4 2 3 5 5 5 2 4 4 5 1 4 4 5 2 4 3 5 1 5 4 2 1 5 3
## [78301] 3 3 2 3 1 2 1 1 3 5 1 5 1 5 4 2 2 3 2 1 4 5 3 4 5 1 1 2 4 2 1 3 2 5 3 2
## [78337] 3 4 5 4 2 4 1 2 3 2 3 4 4 4 1 1 2 5 2 3 4 5 4 4 1 4 2 2 5 1 2 1 2 3 5 4
## [78373] 3 1 3 3 3 1 1 3 2 4 1 4 1 3 3 2 5 5 3 5 2 4 1 3 4 3 1 2 3 1 1 3 4 2 3 5
## [78409] 2 5 3 2 2 1 2 5 1 5 1 2 1 4 3 5 4 1 1 5 1 2 5 4 3 5 1 5 1 4 4 1 3 2 1 4
## [78445] 1 4 3 4 1 2 5 2 2 5 5 4 3 5 5 2 2 2 2 2 2 4 4 4 1 5 4 3 2 1 3 1 5 4 4 3
## [78481] 2 1 5 5 3 3 4 2 2 2 5 5 2 5 1 2 2 5 1 2 1 1 1 5 5 5 5 5 3 1 4 2 1 1 2 4
## [78517] 5 2 5 1 5 5 5 3 5 5 4 4 3 5 1 5 1 5 1 5 5 2 1 1 1 2 2 5 3 2 4 2 2 1 1 1
## [78553] 4 1 2 4 3 1 5 5 2 2 5 3 1 1 3 4 4 3 5 3 4 5 4 1 1 2 5 2 1 2 2 4 3 2 2 1
## [78589] 4 3 3 3 5 5 4 4 5 2 4 3 3 3 2 1 4 1 1 1 4 5 1 1 4 5 2 3 5 5 4 2 4 2 5 4
## [78625] 1 2 5 4 3 1 3 5 5 1 1 5 3 2 3 5 2 1 5 5 2 4 2 1 2 2 5 4 1 4 4 2 2 1 4 1
## [78661] 1 3 2 3 1 1 2 2 5 4 1 3 1 1 2 4 2 2 1 2 1 3 5 5 5 2 1 4 2 3 5 5 1 2 4 4
## [78697] 2 3 3 1 5 2 1 3 4 3 5 1 5 3 3 1 2 3 2 1 2 2 5 1 3 2 5 1 5 1 1 3 4 1 5 3
## [78733] 4 5 5 1 1 1 3 5 4 5 4 3 5 2 5 2 3 1 5 3 4 2 3 5 3 2 5 4 5 2 4 1 4 2 5 1
## [78769] 5 4 2 3 2 5 3 4 4 2 4 1 4 4 2 2 5 2 1 2 4 1 3 2 3 1 5 3 5 1 5 1 4 5 2 4
## [78805] 5 1 2 1 4 5 1 3 4 4 4 4 2 3 4 3 3 2 5 4 2 5 4 1 2 4 3 2 5 3 2 1 2 1 1 2
## [78841] 4 3 1 1 5 3 2 3 1 4 2 5 4 5 5 5 2 4 1 4 1 3 3 1 5 2 4 4 1 4 2 2 5 5 2 3
## [78877] 4 5 4 4 2 4 3 1 5 5 1 4 3 4 5 1 1 1 2 4 3 3 4 5 1 4 5 3 5 4 4 1 1 2 2 3
## [78913] 3 1 5 3 3 2 1 3 4 2 5 3 3 1 4 1 2 5 4 5 4 3 2 4 5 5 4 3 1 1 3 3 4 5 2 3
## [78949] 5 5 1 5 3 4 3 5 2 2 5 2 4 2 3 5 4 3 1 1 5 3 3 1 1 1 1 1 2 4 5 1 4 1 1 4
## [78985] 5 1 4 3 4 1 3 4 2 2 4 4 1 5 3 5 2 5 4 4 3 3 4 4 3 3 5 3 5 5 4 4 3 2 2 1
## [79021] 4 4 5 5 3 3 4 2 5 3 3 3 2 4 1 2 1 1 4 3 3 5 2 5 5 4 3 4 1 1 3 3 4 3 4 3
## [79057] 5 2 5 2 4 3 4 4 5 5 2 1 3 5 1 2 3 3 4 5 3 2 2 3 4 4 4 5 5 3 5 3 3 3 5 1
## [79093] 1 2 3 1 4 4 2 1 1 3 5 3 1 2 2 2 2 1 5 1 3 5 1 2 3 3 3 1 3 5 2 5 4 5 2 3
## [79129] 2 4 1 5 1 5 2 1 5 5 2 2 5 4 4 5 1 5 5 4 2 2 1 1 2 4 2 1 2 5 5 1 3 5 4 1
## [79165] 4 4 2 1 3 1 3 1 5 5 2 4 1 1 4 2 2 5 2 4 3 4 1 3 1 1 4 5 2 4 2 3 5 3 4 5
## [79201] 2 2 1 3 2 2 5 2 1 5 2 2 4 5 1 4 3 3 1 5 1 4 4 2 2 2 4 3 1 4 3 2 1 4 1 1
## [79237] 1 4 1 2 5 5 3 2 3 4 5 4 1 5 2 4 4 2 1 4 4 2 3 3 3 4 3 2 1 5 1 4 2 1 3 2
## [79273] 1 5 4 5 2 4 3 3 1 2 4 2 4 1 5 2 3 3 3 5 1 2 2 1 5 3 1 3 2 3 3 3 4 3 5 5
## [79309] 2 3 4 4 4 5 2 3 4 1 5 5 5 4 2 3 4 1 3 4 2 3 4 5 4 3 1 5 4 5 4 2 5 5 1 2
## [79345] 4 4 2 3 2 1 5 2 4 5 5 2 1 4 1 2 4 2 4 1 1 3 5 1 3 5 1 4 2 2 1 4 5 2 5 5
## [79381] 3 5 3 1 4 2 4 1 2 2 5 5 3 4 3 4 5 3 4 4 1 5 2 2 3 1 1 3 5 4 5 1 3 1 3 3
## [79417] 1 4 3 1 5 4 1 3 5 5 4 3 1 4 4 3 5 2 4 5 1 4 3 2 2 3 5 3 5 2 2 4 2 5 4 3
## [79453] 4 5 4 4 2 5 3 2 3 2 3 1 2 5 2 4 1 1 5 2 2 5 3 1 3 5 3 4 1 4 2 1 5 4 3 1
## [79489] 2 1 1 2 1 3 1 4 4 4 4 2 2 4 5 5 3 4 4 2 5 2 1 2 2 2 1 4 1 2 2 4 5 1 2 2
## [79525] 2 5 1 5 4 5 4 2 1 5 2 2 4 2 2 1 4 3 1 3 4 3 5 4 5 1 1 3 5 1 4 4 5 2 3 4
## [79561] 3 3 1 5 3 2 1 2 4 5 4 2 4 3 5 1 2 2 2 4 3 2 2 1 4 4 3 1 3 2 4 2 1 4 5 1
## [79597] 2 1 1 3 3 2 2 2 5 4 2 3 4 5 1 5 3 4 2 3 2 3 2 4 2 3 5 2 2 1 3 5 5 5 2 2
## [79633] 2 3 4 4 4 2 5 1 3 4 4 5 2 1 4 2 4 4 3 4 3 2 2 1 2 1 1 4 1 5 4 2 1 4 1 3
## [79669] 5 2 2 2 3 4 2 5 4 2 5 5 5 2 5 2 1 4 2 1 4 3 4 2 1 5 1 3 3 5 4 2 2 5 2 3
## [79705] 2 2 1 3 5 3 1 3 2 3 2 1 1 3 5 4 4 5 1 5 5 2 2 3 5 5 2 3 2 4 1 3 5 5 1 4
## [79741] 3 3 4 1 1 3 5 1 5 2 3 5 4 4 2 3 4 5 5 2 1 2 5 2 2 4 3 1 3 3 2 1 2 2 4 5
## [79777] 2 3 4 3 2 1 2 1 4 5 4 2 4 3 1 4 2 1 1 1 2 4 4 1 4 4 4 2 2 3 1 1 5 5 1 2
## [79813] 4 2 4 3 3 5 5 5 2 5 4 2 1 2 5 3 1 1 1 3 5 5 5 2 2 2 3 1 1 4 3 1 1 4 2 3
## [79849] 2 1 5 3 4 4 5 1 1 2 3 1 1 4 5 5 5 3 5 4 4 3 4 3 5 5 2 4 2 5 4 1 3 3 3 2
## [79885] 1 2 5 5 3 1 3 3 5 2 3 1 1 5 5 2 2 4 2 4 1 4 3 3 2 5 1 1 2 4 5 4 2 1 3 2
## [79921] 3 2 2 5 4 2 2 2 5 1 5 2 1 3 5 5 5 4 2 3 5 1 4 5 1 3 5 3 3 1 5 5 4 2 4 2
## [79957] 4 4 1 1 5 5 5 5 2 4 3 5 4 3 5 2 5 4 1 4 1 5 1 2 1 3 3 3 5 1 3 2 3 3 5 1
## [79993] 3 3 2 5 3 3 1 1 2 4 4 3 5 3 1 1 2 4 1 4 2 1 5 5 3 1 1 2 4 5 1 5 1 4 3 1
## [80029] 5 5 2 2 3 3 3 2 1 2 5 2 5 1 2 1 2 2 3 1 2 3 3 5 5 5 5 4 4 5 2 3 4 5 1 1
## [80065] 3 3 4 1 3 4 1 1 1 3 4 1 1 5 1 5 4 2 3 5 3 4 1 1 1 3 4 5 5 1 3 5 3 4 1 2
## [80101] 1 5 3 2 3 4 2 3 3 1 3 4 1 5 2 1 3 4 3 5 5 3 2 1 5 3 2 1 3 4 5 1 1 3 2 2
## [80137] 1 4 2 3 2 3 3 4 1 4 1 2 4 2 4 1 3 1 3 3 1 5 2 5 3 2 3 4 1 1 4 2 5 3 1 3
## [80173] 2 1 1 4 1 1 1 4 2 3 2 2 3 5 5 3 3 5 5 2 3 4 3 1 1 4 4 2 4 2 2 4 1 1 1 3
## [80209] 4 1 3 4 2 2 2 4 5 4 2 1 3 1 2 2 2 2 3 4 4 3 3 5 3 2 3 5 2 4 3 2 4 3 5 3
## [80245] 5 1 2 5 3 1 2 4 2 2 1 5 4 5 3 2 4 2 4 4 5 3 3 4 4 1 1 4 1 2 5 4 5 1 3 3
## [80281] 1 1 3 1 4 1 2 3 1 5 3 3 2 5 2 2 1 1 4 1 4 1 5 1 2 5 2 2 2 5 2 2 5 5 2 3
## [80317] 3 2 3 2 1 1 1 3 1 2 5 1 2 1 3 4 1 2 1 2 5 1 5 1 5 4 4 2 4 1 5 2 2 1 3 5
## [80353] 1 2 3 4 5 1 2 3 4 3 5 3 4 5 4 1 5 4 2 4 4 5 5 3 5 5 3 4 1 2 2 1 2 4 5 3
## [80389] 5 2 3 3 2 3 5 1 2 1 2 3 4 1 2 3 2 4 4 4 2 2 5 3 5 5 4 5 4 4 5 1 1 4 1 4
## [80425] 2 2 1 3 3 3 1 2 2 1 4 1 3 3 5 2 5 2 3 1 1 2 3 5 4 3 2 5 3 5 5 5 4 5 1 5
## [80461] 2 5 1 5 4 3 2 3 1 3 1 3 2 3 5 4 5 1 1 1 5 4 1 1 3 4 3 3 5 4 3 4 2 2 5 2
## [80497] 5 5 2 4 4 5 4 3 3 2 3 3 5 4 5 5 5 4 5 3 2 5 5 3 4 5 2 3 4 4 4 1 3 3 2 4
## [80533] 4 4 2 4 4 2 5 2 5 5 3 1 2 3 1 5 1 5 3 3 5 1 1 3 2 2 1 5 3 3 5 5 4 3 5 1
## [80569] 3 5 1 3 1 4 2 1 1 1 4 3 3 4 2 2 1 2 5 2 4 4 5 2 1 5 3 2 1 5 1 5 4 4 4 3
## [80605] 1 1 1 2 2 3 4 1 3 1 1 4 1 4 4 5 2 2 3 5 2 2 2 2 3 5 4 1 4 2 5 1 5 3 4 1
## [80641] 5 3 4 3 2 5 4 3 5 4 1 4 1 1 5 5 2 4 3 4 1 4 2 4 3 1 3 1 4 1 2 2 2 4 2 1
## [80677] 3 4 4 3 1 3 3 2 3 1 4 3 3 3 3 1 4 4 5 3 5 5 5 1 5 4 3 3 5 4 2 3 5 3 5 4
## [80713] 4 2 5 2 4 3 4 1 1 3 2 3 5 5 3 3 4 4 1 1 5 5 3 3 4 4 5 4 2 1 3 3 3 5 5 4
## [80749] 2 4 1 1 1 4 3 1 2 3 5 1 3 1 3 3 5 2 2 3 5 4 3 2 5 1 4 1 1 5 4 5 3 2 1 2
## [80785] 5 5 2 4 1 4 4 5 5 3 2 5 3 4 1 1 5 5 2 5 3 2 2 5 5 1 4 4 2 4 3 1 5 2 5 3
## [80821] 1 4 5 5 5 5 5 4 4 2 2 3 4 4 4 2 1 4 4 4 5 3 1 5 4 2 1 5 2 4 3 2 2 3 5 3
## [80857] 4 4 4 5 5 1 4 3 4 5 1 3 2 2 5 3 4 4 4 3 4 4 5 4 3 5 1 5 5 2 1 5 2 3 1 2
## [80893] 4 2 4 3 1 2 1 3 2 5 4 2 2 5 4 3 5 5 5 4 4 4 2 3 1 3 2 2 1 4 3 2 4 3 5 5
## [80929] 3 3 3 1 1 3 4 2 4 3 3 1 3 2 2 3 3 5 1 1 3 2 2 4 3 4 5 3 5 1 2 4 5 2 4 1
## [80965] 1 2 4 5 5 3 3 3 2 5 5 2 3 5 1 5 5 2 5 5 4 1 4 1 5 3 2 2 4 5 2 4 1 1 4 1
## [81001] 2 4 4 2 1 3 4 5 5 4 2 1 4 4 5 3 2 1 5 3 2 1 3 3 3 1 4 1 4 4 3 2 4 3 4 2
## [81037] 2 2 4 4 2 3 5 3 4 2 5 1 2 5 2 2 5 3 2 3 4 1 5 3 5 1 5 4 5 3 2 2 2 5 4 2
## [81073] 2 3 5 5 3 3 1 1 5 5 5 1 2 2 1 5 2 4 4 2 1 4 3 1 2 2 5 3 2 2 3 3 5 4 5 5
## [81109] 2 3 2 2 3 5 4 4 3 5 1 1 2 1 1 1 3 2 4 2 5 4 3 2 2 4 2 5 2 3 5 3 2 5 3 5
## [81145] 1 3 4 5 1 5 1 3 2 1 5 5 5 4 5 5 2 3 3 3 4 3 3 3 5 1 3 3 3 1 5 4 2 1 4 3
## [81181] 4 1 1 4 1 2 1 5 2 5 2 2 3 2 3 2 3 4 5 4 1 1 5 4 3 2 1 5 4 4 4 1 5 3 3 2
## [81217] 5 2 3 3 1 4 5 5 1 3 1 5 5 2 4 3 4 3 4 5 5 1 4 3 5 2 4 3 3 2 1 4 5 2 3 1
## [81253] 1 3 2 4 2 1 2 1 3 1 3 4 1 5 4 4 5 2 5 1 4 5 1 3 1 3 1 4 5 1 2 2 4 4 5 3
## [81289] 5 1 4 4 4 3 3 5 4 4 1 1 5 4 1 2 3 4 3 5 2 2 4 3 2 2 4 3 2 3 5 4 4 3 5 3
## [81325] 2 5 2 4 4 2 2 4 3 3 2 3 4 1 1 1 2 2 1 3 3 4 2 5 1 4 2 1 4 4 5 4 4 2 3 2
## [81361] 2 3 1 2 1 3 4 3 2 5 1 1 4 1 3 4 1 4 1 2 5 5 4 3 3 1 2 2 3 5 3 4 2 4 2 1
## [81397] 5 2 2 3 1 4 2 2 3 5 1 5 4 5 5 3 4 1 1 5 2 2 4 3 1 4 1 5 5 2 5 3 3 4 5 4
## [81433] 5 3 1 5 3 5 1 3 1 4 2 3 1 3 2 3 1 3 4 3 5 1 5 2 1 1 2 1 1 1 2 5 4 4 2 4
## [81469] 1 3 3 3 1 4 4 2 1 3 1 5 1 5 5 1 4 2 3 1 2 2 3 2 5 4 5 5 2 2 4 4 1 3 1 5
## [81505] 4 4 3 3 1 5 3 1 3 5 4 1 5 5 4 3 2 5 1 4 1 1 2 4 3 4 4 2 1 5 2 1 1 4 1 3
## [81541] 5 4 3 3 4 4 5 5 3 4 1 2 5 4 2 5 1 2 5 5 4 5 1 4 5 4 3 4 4 1 4 1 1 5 1 3
## [81577] 4 2 2 1 3 3 2 2 3 1 2 4 3 4 1 3 4 1 2 4 3 5 3 4 5 5 2 1 2 4 2 1 2 1 2 3
## [81613] 5 5 3 3 1 2 1 2 1 5 5 5 1 1 5 2 3 3 1 2 5 2 4 5 3 5 5 4 2 4 2 4 4 2 5 5
## [81649] 5 5 5 3 2 2 1 1 2 5 1 4 2 2 2 1 1 4 4 2 5 3 3 2 2 1 3 2 1 5 3 1 5 5 3 1
## [81685] 3 2 4 3 5 3 4 2 4 2 5 4 2 2 5 4 4 5 3 5 1 2 2 2 1 3 3 1 5 4 4 4 2 1 5 3
## [81721] 1 5 2 3 5 2 4 1 3 3 4 1 5 4 2 1 3 2 1 2 3 3 4 1 1 4 1 3 1 3 4 1 5 4 2 5
## [81757] 3 2 2 1 1 5 4 5 5 5 3 1 2 4 5 3 1 1 2 3 1 2 1 2 4 4 5 4 5 2 5 4 2 4 2 5
## [81793] 1 1 1 3 3 4 2 5 1 2 5 2 3 1 2 3 4 3 5 3 1 5 1 5 2 1 5 4 1 1 2 3 4 5 3 5
## [81829] 2 2 2 5 1 2 3 1 3 2 3 5 2 5 1 3 5 5 1 1 5 5 5 1 4 4 4 2 3 4 2 3 2 1 3 5
## [81865] 1 5 1 5 2 3 1 5 3 4 4 4 1 3 1 1 2 1 4 2 5 4 4 2 3 5 2 3 4 3 4 5 3 1 3 2
## [81901] 2 3 2 3 4 4 3 3 5 2 2 1 5 2 4 2 4 4 2 3 2 2 2 2 5 2 3 1 1 1 2 4 4 1 2 3
## [81937] 2 3 5 3 4 4 2 2 3 5 5 5 5 5 1 4 4 4 2 3 3 1 5 1 3 5 5 2 4 2 1 2 1 3 5 5
## [81973] 2 4 3 1 4 1 4 4 4 2 2 1 3 1 1 4 1 5 5 2 2 5 4 5 3 3 1 1 4 1 3 5 2 2 5 3
## [82009] 2 2 3 4 5 2 1 1 1 4 3 2 5 2 3 2 4 2 3 2 4 4 4 3 5 4 5 1 2 2 3 4 4 3 1 1
## [82045] 1 2 5 4 4 1 2 3 4 1 4 3 4 2 3 3 5 3 1 3 4 4 3 3 5 1 5 2 1 1 5 2 1 5 4 4
## [82081] 4 3 1 2 3 4 2 5 3 2 1 5 3 5 3 4 2 2 1 3 3 1 1 4 4 3 5 1 3 3 1 1 5 3 5 5
## [82117] 1 3 3 2 3 2 2 4 3 3 2 2 2 5 4 3 3 2 5 4 1 1 4 5 3 4 5 3 5 2 3 2 3 1 3 1
## [82153] 5 1 1 4 1 5 3 3 4 2 2 2 2 5 5 5 3 2 3 4 3 4 3 3 3 3 5 5 1 4 2 3 4 2 4 1
## [82189] 3 3 1 4 3 5 1 3 4 3 2 5 1 4 2 5 2 5 2 1 2 5 3 1 4 4 2 1 2 4 4 2 3 1 5 3
## [82225] 5 4 2 2 1 5 1 3 3 1 3 5 1 1 2 4 4 2 5 4 5 4 5 3 2 3 4 4 1 5 1 2 4 3 3 2
## [82261] 4 5 3 2 1 4 4 2 2 2 2 5 4 4 1 1 5 3 4 1 5 5 3 5 4 1 1 3 1 2 2 5 2 1 3 5
## [82297] 4 2 3 4 5 2 3 5 5 3 4 3 4 1 4 1 1 3 2 2 2 2 5 1 3 2 5 5 4 4 1 2 5 1 3 1
## [82333] 1 1 3 4 3 5 5 2 2 4 2 2 3 1 3 1 5 4 4 1 1 4 2 3 2 1 4 3 1 1 3 1 4 1 1 5
## [82369] 3 2 5 1 1 5 3 4 4 3 3 1 1 1 3 5 5 5 5 5 2 5 2 4 5 4 1 3 1 3 1 3 1 4 1 1
## [82405] 2 1 3 2 3 1 5 5 5 1 1 1 3 2 2 5 5 3 2 3 2 3 1 5 5 3 1 3 1 5 4 3 1 2 4 2
## [82441] 5 3 3 4 2 2 5 4 5 5 1 4 1 2 1 1 1 4 1 1 4 4 5 5 3 2 1 4 5 5 1 2 3 5 4 3
## [82477] 2 5 1 5 1 5 5 1 4 1 2 1 1 4 3 4 5 5 5 2 4 5 3 5 5 5 4 2 3 3 5 2 2 1 5 3
## [82513] 1 4 4 4 1 5 2 3 4 2 3 5 5 2 3 2 1 5 2 3 3 4 3 2 1 1 4 1 1 2 2 3 1 1 1 3
## [82549] 3 3 5 3 1 4 3 1 2 5 2 2 3 4 4 2 4 3 5 5 2 1 5 1 2 2 1 4 2 3 2 5 1 5 1 3
## [82585] 2 1 2 2 4 1 2 2 4 3 4 5 2 2 4 5 1 2 4 4 5 1 5 5 4 5 5 5 1 2 2 5 2 2 2 2
## [82621] 4 4 2 1 5 2 3 5 5 1 1 2 5 3 3 1 1 1 5 3 3 5 2 5 3 4 2 5 1 1 2 5 3 1 4 3
## [82657] 1 4 1 4 5 2 4 4 2 2 3 4 3 1 5 2 2 4 4 5 2 1 5 1 2 3 1 1 5 3 1 2 1 3 1 5
## [82693] 3 5 4 5 4 2 3 1 3 3 4 5 3 1 1 5 5 2 5 3 5 4 2 4 5 3 1 3 1 2 4 5 5 1 1 5
## [82729] 2 1 1 5 4 5 3 3 3 4 5 1 4 4 1 2 1 4 3 4 4 1 5 2 1 4 4 5 3 2 3 4 4 1 3 3
## [82765] 1 1 2 4 5 3 3 2 5 2 2 5 4 1 1 3 3 4 1 4 1 3 4 2 2 4 2 5 1 3 2 1 4 4 1 2
## [82801] 1 3 5 3 5 1 4 3 4 4 2 3 3 4 3 3 5 1 4 2 5 2 1 3 4 5 2 3 4 1 2 3 2 4 1 5
## [82837] 5 5 5 1 3 3 5 2 1 2 1 1 2 1 3 1 4 5 2 4 1 2 5 5 4 4 2 5 2 3 4 3 3 1 1 3
## [82873] 2 4 4 2 3 1 4 4 4 1 4 5 4 1 5 5 1 2 3 1 4 4 5 2 3 1 3 5 3 5 3 4 3 3 3 1
## [82909] 4 4 4 4 2 4 1 5 3 2 3 1 1 2 4 5 1 5 5 2 4 4 3 4 4 3 1 1 4 4 3 5 3 5 4 3
## [82945] 5 1 4 1 5 5 2 3 3 2 3 1 1 3 2 5 4 5 3 3 3 2 4 1 3 2 3 5 5 4 2 2 4 4 1 3
## [82981] 2 1 5 2 5 4 5 4 3 4 2 2 1 1 3 1 4 3 1 3 4 2 3 5 1 1 3 3 4 1 5 2 4 1 3 4
## [83017] 4 5 5 4 3 3 1 3 2 5 1 3 3 4 4 3 5 3 3 3 1 2 5 5 2 5 3 5 4 2 4 4 3 3 5 1
## [83053] 2 5 1 2 4 1 1 4 2 1 5 1 3 3 4 3 1 3 5 2 2 1 2 3 4 5 2 5 3 2 2 4 4 5 1 3
## [83089] 2 1 2 2 5 1 2 2 4 1 2 4 4 2 5 3 2 5 1 5 5 2 5 2 1 2 2 4 1 4 1 2 4 2 5 5
## [83125] 4 1 4 4 2 5 1 5 1 5 4 5 1 2 2 2 3 5 1 4 4 4 3 5 2 1 1 5 5 3 5 3 1 2 5 3
## [83161] 4 5 2 4 4 4 1 4 1 1 3 4 2 3 5 4 4 4 5 3 5 3 4 2 3 4 1 1 4 2 1 4 1 2 3 3
## [83197] 4 3 1 1 3 2 5 4 5 3 4 1 4 4 3 1 1 3 4 4 4 5 1 1 1 5 4 2 4 2 5 3 2 4 2 1
## [83233] 3 2 2 4 2 3 4 3 2 5 3 5 5 1 4 2 1 4 4 4 5 2 3 4 3 3 3 2 2 4 4 3 4 5 4 2
## [83269] 5 3 3 3 5 2 5 5 2 5 2 3 3 5 2 2 2 4 1 1 2 5 3 2 2 5 1 4 4 3 5 5 4 2 5 2
## [83305] 4 2 4 1 1 3 5 1 1 2 5 5 5 5 1 5 1 3 1 2 2 3 3 2 4 3 3 1 4 2 2 3 5 3 3 4
## [83341] 4 1 2 5 2 5 4 4 1 4 1 5 2 5 5 5 1 2 5 5 4 1 4 5 2 5 2 3 3 5 1 3 4 5 4 1
## [83377] 2 5 5 4 5 1 5 4 2 4 4 2 5 1 5 5 3 3 4 2 2 2 5 1 5 2 5 3 4 2 3 3 5 1 3 4
## [83413] 1 1 5 1 4 4 5 4 5 5 2 5 1 1 5 2 4 2 3 1 5 1 2 2 1 5 4 2 3 3 2 1 2 2 5 4
## [83449] 2 5 4 1 1 1 5 3 2 1 5 4 3 4 3 3 5 4 2 4 3 3 5 5 5 5 2 2 3 3 2 5 4 3 5 1
## [83485] 1 1 4 4 5 2 4 3 3 2 3 2 4 2 4 2 3 5 5 1 3 3 2 4 5 5 1 3 3 4 2 2 1 2 1 1
## [83521] 5 3 5 2 1 3 3 1 1 4 3 4 1 3 2 2 3 1 5 3 5 2 5 4 3 5 5 2 2 1 1 5 3 2 3 4
## [83557] 2 3 2 4 2 5 1 3 1 4 1 5 5 2 2 5 1 5 3 3 4 4 3 1 4 5 4 1 2 3 3 5 2 5 3 1
## [83593] 4 3 5 4 2 5 2 5 3 4 1 5 3 4 5 3 5 2 2 3 2 3 3 1 5 4 5 2 5 5 3 3 5 4 2 3
## [83629] 3 1 4 4 5 2 1 1 3 5 5 2 2 2 4 5 1 3 4 3 4 3 3 4 1 3 3 2 4 2 5 5 1 4 2 5
## [83665] 5 3 4 3 5 1 2 1 5 5 3 2 3 3 2 3 5 5 1 5 5 2 4 2 3 2 5 2 4 3 3 4 2 1 4 3
## [83701] 2 2 4 2 5 3 2 5 5 3 5 1 1 3 5 2 2 1 4 2 5 4 5 5 3 2 1 5 2 3 4 5 5 1 4 3
## [83737] 2 2 2 5 2 2 3 4 2 2 4 4 5 5 4 3 3 5 5 5 3 5 4 5 1 2 3 2 4 1 5 4 3 1 2 4
## [83773] 5 5 4 2 1 5 1 5 2 1 4 1 1 3 1 4 2 2 2 3 3 4 2 4 4 5 3 4 3 3 3 4 4 3 5 5
## [83809] 4 4 1 2 5 3 5 5 2 3 1 5 3 4 1 2 5 2 1 1 1 1 3 2 3 5 1 3 3 5 5 1 4 4 4 5
## [83845] 5 2 2 5 4 4 2 2 3 1 3 4 5 2 3 4 3 1 2 2 1 3 5 5 1 4 5 3 2 3 2 4 2 4 2 3
## [83881] 1 1 2 1 4 5 5 3 5 3 2 3 1 4 5 5 5 5 1 1 5 3 2 1 4 4 2 2 1 3 5 4 2 3 2 5
## [83917] 5 3 4 2 2 2 1 5 5 3 2 3 3 4 5 1 5 4 4 1 3 3 1 3 3 2 4 4 1 2 5 2 3 1 3 2
## [83953] 5 4 5 2 3 4 5 5 5 1 3 1 4 4 3 1 3 3 5 2 2 1 5 5 2 2 5 5 2 1 2 5 4 2 1 5
## [83989] 3 3 1 1 4 4 1 4 2 2 2 1 5 3 4 2 2 3 5 4 2 1 5 4 5 2 5 5 2 2 1 1 1 3 2 4
## [84025] 5 2 5 1 5 5 2 3 5 1 2 1 5 4 2 5 3 4 1 3 3 5 2 2 4 2 5 3 1 3 4 1 3 5 3 5
## [84061] 3 5 3 1 4 2 3 3 1 1 3 4 1 1 3 5 4 1 1 5 1 4 4 2 3 4 5 1 5 2 4 2 1 2 4 5
## [84097] 1 4 1 2 4 5 3 4 4 5 2 3 1 5 2 1 5 2 4 1 4 4 4 1 2 3 4 1 4 2 5 4 1 5 2 4
## [84133] 1 2 4 5 3 5 1 4 2 5 4 3 1 5 4 2 2 2 5 3 1 4 5 3 5 3 3 4 4 3 4 3 1 3 4 4
## [84169] 4 2 4 3 1 3 3 5 1 2 4 5 4 4 1 1 4 4 5 3 3 3 4 1 4 5 4 3 5 2 3 2 4 1 2 1
## [84205] 3 5 5 3 1 2 4 2 2 2 5 3 4 4 3 3 4 4 3 1 3 5 1 1 5 3 1 3 1 5 5 5 3 1 5 1
## [84241] 1 3 4 1 3 3 5 5 1 2 1 3 2 1 5 4 5 3 2 5 4 3 1 2 5 3 4 5 4 5 2 3 3 1 1 2
## [84277] 1 1 2 3 4 5 1 4 5 3 3 2 5 4 5 2 5 5 1 4 4 3 3 1 3 4 5 4 1 5 4 3 1 1 4 4
## [84313] 4 2 2 3 3 2 3 1 4 1 4 3 4 1 1 4 2 1 2 3 2 5 2 3 2 2 5 1 3 4 2 4 4 3 4 3
## [84349] 4 5 1 4 4 3 3 4 4 4 3 4 1 4 1 5 1 1 3 1 2 3 2 2 2 5 3 1 3 4 1 1 3 3 5 2
## [84385] 5 2 2 5 5 1 5 5 1 3 4 5 1 1 3 3 2 1 3 4 4 4 4 3 3 2 3 5 4 5 2 4 4 4 3 4
## [84421] 4 4 3 1 4 2 5 2 4 4 3 3 5 3 1 3 4 3 5 1 4 3 4 1 5 1 4 5 4 3 2 4 4 2 2 5
## [84457] 4 3 3 2 5 5 2 3 5 3 3 5 2 4 3 1 4 2 4 5 3 3 4 3 5 2 2 1 3 1 2 5 1 5 2 1
## [84493] 4 1 3 4 4 4 3 4 4 4 2 4 2 4 4 5 1 5 3 5 3 5 4 3 3 2 1 4 2 5 3 1 2
# Set error.folds (a vector) to save validation errors in future
error.folds = NULL
# Set seed since do.chunk() contains a random component induced by knn()
set.seed(888)
# Loop through different chunk id
for (i in seq(5)){
  tmp = do.chunk.bart(chunkid=i, folddef=folds, Xdat=Xtrainbart, Ydat=Ytrainbart)
  error.folds = rbind(error.folds, tmp)
}
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 67620
## y1,yn: 0.247713, -2.708945
## x1,x[n*p]: -0.300382, -3.309939
## xp1,xp[np*p]: -0.300382, -3.309939
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.109079,3,0.0616128,-0.00176647
## *****sigma: 0.562407
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 373s
## trcnt,tecnt: 1000,1000
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 16905
## y1,yn: 0.247713, -2.708945
## x1,x[n*p]: -0.300382, -3.309939
## xp1,xp[np*p]: -0.776096, -3.152919
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.109079,3,0.0616128,-0.00176647
## *****sigma: 0.562407
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 324s
## trcnt,tecnt: 1000,1000
## Warning in Ytrainbart - predYtr$yhat.train.mean: longer object length is not a
## multiple of shorter object length
## Warning in Ytestbart - predYval$yhat.test.mean: longer object length is not a
## multiple of shorter object length
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 67620
## y1,yn: 0.248069, -2.580040
## x1,x[n*p]: -0.300382, -3.152919
## xp1,xp[np*p]: -0.300382, -3.152919
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.113624,3,0.0614822,-0.00212197
## *****sigma: 0.561810
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 366s
## trcnt,tecnt: 1000,1000
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 16905
## y1,yn: 0.248069, -2.580040
## x1,x[n*p]: -0.300382, -3.152919
## xp1,xp[np*p]: 0.313443, -3.309939
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.113624,3,0.0614822,-0.00212197
## *****sigma: 0.561810
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 317s
## trcnt,tecnt: 1000,1000
## Warning in Ytrainbart - predYtr$yhat.train.mean: longer object length is not a
## multiple of shorter object length

## Warning in Ytrainbart - predYtr$yhat.train.mean: longer object length is not a
## multiple of shorter object length
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 67620
## y1,yn: 0.246286, -2.710373
## x1,x[n*p]: -0.300382, -3.309939
## xp1,xp[np*p]: -0.300382, -3.309939
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.113624,3,0.0611811,-0.000338771
## *****sigma: 0.560433
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 364s
## trcnt,tecnt: 1000,1000
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 16905
## y1,yn: 0.246286, -2.710373
## x1,x[n*p]: -0.300382, -3.309939
## xp1,xp[np*p]: 0.535954, 2.100115
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.113624,3,0.0611811,-0.000338771
## *****sigma: 0.560433
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 321s
## trcnt,tecnt: 1000,1000
## Warning in Ytrainbart - predYtr$yhat.train.mean: longer object length is not a
## multiple of shorter object length

## Warning in Ytrainbart - predYtr$yhat.train.mean: longer object length is not a
## multiple of shorter object length
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 67620
## y1,yn: -1.748366, -2.712494
## x1,x[n*p]: 0.535954, -3.309939
## xp1,xp[np*p]: 0.535954, -3.309939
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.113624,3,0.0611696,0.00178187
## *****sigma: 0.560381
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 377s
## trcnt,tecnt: 1000,1000
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 16905
## y1,yn: -1.748366, -2.712494
## x1,x[n*p]: 0.535954, -3.309939
## xp1,xp[np*p]: -0.300382, 2.100115
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.113624,3,0.0611696,0.00178187
## *****sigma: 0.560381
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 319s
## trcnt,tecnt: 1000,1000
## Warning in Ytrainbart - predYtr$yhat.train.mean: longer object length is not a
## multiple of shorter object length

## Warning in Ytrainbart - predYtr$yhat.train.mean: longer object length is not a
## multiple of shorter object length
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 67620
## y1,yn: 0.243501, -2.713157
## x1,x[n*p]: -0.300382, -3.309939
## xp1,xp[np*p]: -0.300382, -3.309939
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.113624,3,0.0615526,0.00244535
## *****sigma: 0.562132
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 362s
## trcnt,tecnt: 1000,1000
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 67620, 14, 16905
## y1,yn: 0.243501, -2.713157
## x1,x[n*p]: -0.300382, -3.309939
## xp1,xp[np*p]: 1.318581, 2.100115
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.113624,3,0.0615526,0.00244535
## *****sigma: 0.562132
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 315s
## trcnt,tecnt: 1000,1000
## Warning in Ytrainbart - predYtr$yhat.train.mean: longer object length is not a
## multiple of shorter object length

## Warning in Ytrainbart - predYtr$yhat.train.mean: longer object length is not a
## multiple of shorter object length
head(error.folds)
##   fold train.error val.error
## 1    1    1.675521  1.700420
## 2    2    1.667937  1.696768
## 3    3    1.676415  1.675462
## 4    4    1.681904  1.688077
## 5    5    1.695250  1.700255

Finally, we were able to get the test MSE after we iterated through a 5-fold cross validation.

pred.YTest = gbart(Xtrainbart, Ytrainbart, x.test = Xtestbart)
## *****Calling gbart: type=1
## *****Data:
## data:n,p,np: 84525, 14, 36225
## y1,yn: 0.245947, -2.710712
## x1,x[n*p]: -0.300382, -3.309939
## xp1,xp[np*p]: 1.166057, -0.488517
## *****Number of Trees: 200
## *****Number of Cut Points: 100 ... 100
## *****burn,nd,thin: 100,1000,1
## *****Prior:beta,alpha,tau,nu,lambda,offset: 2,0.95,0.113624,3,0.0613989,1.93755e-16
## *****sigma: 0.561430
## *****w (weights): 1.000000 ... 1.000000
## *****Dirichlet:sparse,theta,omega,a,b,rho,augment: 0,0,1,0.5,1,14,0
## *****printevery: 100
## 
## MCMC
## done 0 (out of 1100)
## done 100 (out of 1100)
## done 200 (out of 1100)
## done 300 (out of 1100)
## done 400 (out of 1100)
## done 500 (out of 1100)
## done 600 (out of 1100)
## done 700 (out of 1100)
## done 800 (out of 1100)
## done 900 (out of 1100)
## done 1000 (out of 1100)
## time: 429s
## trcnt,tecnt: 1000,1000
# Test mse
test_mse = mean((Ytestbart - pred.YTest$yhat.test.mean)^2)
test_mse
## [1] 0.3012486

Because the test error was quite high, we decided to check if boosting had a better prediction. To do this, we fit a boosting model.

# Test error was quite high for BART, checking if boosting is any better....
#set.seed (1)
#boost.music <- gbm(popularity ~ ., data = train,
  #distribution = "gaussian", n.trees = 1000,
  #interaction.depth = 4)
#yhat.boost <- predict(boost.music ,
  #newdata = train, n.trees = 1000)
#mean ((yhat.boost - Ytestbart)^2)

As we can see [insert the results of the boosting].

Multivariate Additive Regression Splines (MARS)

The final algorithm we implimented was the multivariate adaptive regression splines (MARS). The MARS model is an ensemble of piecewise linear functions that are joined together by hinge functions. This accounts for non-linearity between inputs and outputs. The MARS algorithm has two stages - a forward stage and a backward stage. The forward stage generates many pairs of functions as candidates for the basis of the model. The backward stage is considered the pruning stage - the model goes through all of the functions and deletes the functons that don’t add further value to the model performance.

We chose to use the MARS algorithm because we can see that the relationship between popularity and our predictors is often non-linear. Additionally, we have many predictor variables and the MARS algorithm is capable of achieving good performance on a regression problem with many predictor variables.

In a nutshell, the MARS method works like this: 1. Divide a given dataset into k pieces. 2. Fit a regression model to each piece. 3. Use k-fold cross-validation to choose a value for k.

Our first step was to create a tuning grid for pruning and set a seed for reproductability:

library(earth) # library for fitting MARS models
## Loading required package: Formula
## Loading required package: plotmo
## Loading required package: plotrix
## Loading required package: TeachingDemos
library(caret) # library for tuning the model parameters

trainmars <- train # copy dataset for mars model

#create a tuning grid
hyper_grid <- expand.grid(degree = 1:3,
                          nprune = seq(2, 50, length.out = 10) %>%
                          floor())

#make this example reproducible
set.seed(123)

Next, we fit the model with k-fold cross validation:

#fit MARS model using k-fold cross-validation
cv_mars <- train(
  x = subset(trainmars, select = -c(popularity)),
  y = train$popularity,
  method = "earth",
  metric = "RMSE",
  trControl = trainControl(method = "cv", number = 10),
  tuneGrid = hyper_grid)

Finally, we used the MARS algorithm to find the model with the lowest test RMSE:

#display model with lowest test RMSE
cv_mars$results %>%
  filter(nprune == cv_mars$bestTune$nprune, degree == cv_mars$bestTune$degree)    
##   degree nprune     RMSE  Rsquared      MAE    RMSESD RsquaredSD    MAESD
## 1      3     18 8.621526 0.6928844 6.265727 0.1530968 0.01070354 0.102432

We can see that the best model found by the MARS method was of degree 3 with 18 prunes. The R-squared was 0.6928, which is fairly strong correlation for this mode. The test root mean squared error was 8.6215.

Below is a graph of the test RMSE by terms and degree - one can see that the third degree has the lowest RMSE and the number of terms appear to minimize RMSE at a value between 10 and 20 (hence why our value of 18 makes sense).

#display test RMSE by terms and degree
ggplot(cv_mars)

To compare this model to the other models we fit, we will convert RMSE to MSE:

testmse_mars <- cv_mars$results$RMSE[18]^2
testmse_mars
## [1] 74.33276

Thus, we have a test MSE value of 74.33276 from our model using multivariate adaptive regression splines.

Comparing models

Sources

ISLR (insert page(s)/sections later)

Lab 4 Cross-Validation

elastic net model information

MARS model information

MARS code